HYPOTHESIS

9 Hypothesis

  • Ø9.1 Introduction
  • Ø9.2 Definition of Hypothesis

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  • Ø 9.3 Importance of Hypothesis

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  • Ø 9.4 Types of Hypothesis

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  • Ø 9.5 Procedure of Testing Hypothesis
  • Ø 9.6 Application of Hypothesis in Research
  • Ø 9.7 Five Steps of Hypothesis Testing

9.1/C2 Introduction:

A hypothesis is a tentative generalization, the validity of which has got to be tested. It is typically considered as the principal instrument in research. Its main function is to suggest new experiment and observations. Enthusiastic observation, creative thinking, feeling, unit, imagination, vision, insight and sound judgment are of greater importance in setting up reasonable hypotheses. The formulation of hypotheses plays an important part in the growth of knowledge in every science. The hypotheses are formulated to facilitate the findings of the research study.

(Ghosh, B. N., (1992). Scientific Method and Social Research. 3rd ed. Sterling publisher pvt. Ltd. P. 51-52)

 

9.2/C2 Definition of Hypothesis:

Hypothesis is considered as one of the principle instrument in research. In simplest of words, it is a general idea of the researcher that this may be perhaps the answer to a problem. Generally Hypotheses indicate any tentative solution to a problem. After the verification, when the hypothesis is found to be true, a theory is stabilized.

In the word of Richard D. Crisp, (1957) “A hypothesis may be defined as a tentative theory or supposition set up and adopted provisionally as a guide in the further investigation of other facts or relations.”

According to M.H. Gopal, “A hypothesis is a tentative solution posed on a cursory observation of known and available data and adopted provisionally to explain certain events and to guide in the investigation of others. It is, in fact, a possible solution to the problem.”

In the words of Van Dalen, (1956) “A hypotheses serves as a powerful beacon that lights the way for the research worker.”

From this definition we can get some characteristics of hypothesis this are given below:

v  Hypothesis should be clear and precise.

v  Hypothesis should be capable of being tested.

v  Hypothesis should state relationship between variables.

v  Hypothesis should be consisted with most known facts.

v  Hypothesis should be amenable to testing within a reasonable time.

So, we can analyze the meaning of Hypotheses as a tool of research which

tells the researcher what he has to do, how he has to do and what kind of results be expected, in context of the problem. So the research hypothesis is a predictive statement, capable of being tested by scientific methods, that relates independent variables to some dependent variable. For example, consider statements like the following ones: “Students who receive counseling will show a greater increase in creativity than students not receiving counseling.”

(Kothari, C. R., (1999) Research Methodology Methods & Technique. India: Wishwa Prakashan. P. 223-224)

 

9.3/C2 Importance of Hypothesis

Hypothesis has a great importance in research although it absorbs a very small place in the body of a research. It is almost impossible for a research worker not to have and or more hypotheses before proceeding with his work. The importance of hypothesis can be more specifically stated as under:

v  It Provides direction to research. It defines what is relevant and what is irrelevant. Thus it prevents the appraisal of irrelevant literature and the collection of useless or overload data.

v  It is the investigator’s eye- a sort of guiding light in the world of darkness.

v  It prevents blind research. Prevents haphazard gathering of data which may later turn to be irrelevant.

v  It places clear and specific goals prior to us. These clear and particular goals provide the investigator with a foundation for selecting samples and research procedures to meet these goals.

v  It directs the researcher to collect data in an orderly way.

v  It establishes the relationship between prediction and actual observation.

v  It serves the function of the linking together related facts and information and organizing to them in one comprehensible whole.

v  It enables the investigator to understand clearly with his problem and its consequences, as well as data which beat on it.

v  It serves as a formulation for drawing conclusions. It provides the outline for setting conclusions in a meaningful way.

(Zainul, M., (1996) A Hand Book of Research for the Fellows of M. Phil and Ph. D Programmes. Dhaka: Book Syndicate. P. 23-27)

(Retrieved from:  http://www.scribd.com/doc/29008297/hypothesis#download, On 6th August, 2012.

 

9.4/C2 Types of Hypothesis

Practically to conducting a research work a researcher formulates three types of hypothesis. These are:

  1.        i.            Working Hypothesis
  2.      ii.            Null Hypothesis
  3.   iii.            Alternative or Alternate Hypothesis

Frequently he begins his work with a working hypothesis. These are discussed below-

i. Working Hypothesis:

A working or trial hypothesis is provisionally adopted to explain relationship between some observed facts, for guiding a researcher in the investigation of a problem. Since a researcher, tests it in the light of gathered information/data, it is called trial or working hypothesis. In the word of Wilson Gee (1950), “A statement constitutes a trial or working hypothesis (which) is to be tested, and confirmed, modified or even abandoned as the investigation proceeds.”

Example: Child mortality rate is decreasing because of available medical facilities.

 

ii. Null Hypothesis:

A null hypothesis is formulated against the working hypothesis. So a null hypothesis is contrary to the positive statement made in the working hypothesis. Null hypothesis are formulated for testing statistical significance. When a researcher rejects a null hypothesis, he actually proves a working hypothesis. It is also easy to adapt statistical techniques to test a null hypothesis. In statistics, to mean a null hypothesis, usually ‘Ho’ is used.

For example: Ho: Child mortality rate is not decreasing because of available medical facilities.

iii. Alternate hypothesis:

It is a statement, which is accepted, after a null hypotheses is rejected based on the test result. Researcher develops such a hypothesis when he believes with adequate reasons that the alternative hypothesis explains the phenomenon most efficiently or fits the case best. The notion used to mean alternative hypothesis is ‘H1’.

For example: H1: Child mortality rate is significantly decreasing because of available medical facilities.

 

(Steven D. LeMire, S.D., (2010) An Argument Framework for the Application of Null Hypothesis Statistical Testing in Support of Research, Journal of Statistics Education, 18)

(Zainul, M., (1996) A Hand Book of Research for the Fellows of M. Phil and Ph. D Programmes. Dhaka: Book Syndicate. P. 23-27)

9.5/C2 Procedure of Testing Hypothesis

After formulating of a hypothesis, it has to be tested accurately. For testing a hypothesis, a researcher should first determine the level of significance which various between 5 percent and 1 percent. It means that the coefficient is significantly differently zero at the 1or 5 percent level. It also explains that the alternative hypothesis is acceptable at 99 or 95 percent confidence level. So, the level of significance is a line of separation between rejection and acceptance of a hypothesis. There are five steps involved in testing the reliability of hypothesis. These are briefly discussed below.

 

Step-1: Formulate a Hypothesis:

The first step is to set up two hypotheses instead of one in such that if one hypothesis is true, the other is false. Alternatively, if one hypothesis is false or rejected, the other is true or accepted. That is Ho and H1.

Step-2: Set up a Suitable Significant Level:

Having formulated the hypothesis, the next step test its validity at a certain level of significance. The assurance with which a null hypothesis rejected or accepted depends upon the significance level used for the purpose. A significance level of, say 5%, means that in the long run, the risk of making the wrong decision is about 5%. In other words, one is likely to be wrong in accepting a false hypothesis on 5 out of 100 occasions.  Significance level of, say 1% implies that there is a risk of being wrong in accepting or rejecting the hypothesis on 1 out of 100 occasions. Thus, a 1% significance level provides greater confidence to the decision than a 5% significance level.

Step-3: Select Test Criterion:

The third step in hypothesis testing is the selection of a suitable statistical technique as a test criterion. There are many techniques from which one is to be chosen. For example, when the hypothesis pertains to a large sample of more than 30, implying normal distribution is used. When a sample is small (less than 30), then other test will be more suitable. The test criteria that are frequently used in hypotheses testing are z, t, f & χ2.

 

Step-4: Compute:

After having selected the statistical technique to test the hypotheses accurately, the next step involves various computations for the application of that particular test. These computations include the testing statistics as its standard error.

 

Step-5: Make Decisions:

The final step in hypothesis testing is to draw a statistical decision, involving the acceptance or rejection of the null hypothesis. This will depend on whether the computed value of the test criterion falls in the region of acceptance or in the region of rejection at a given level of significance. It may be noted that the statement rejecting the hypothesis is much stronger than the statement accepting it. It is much easier to prove something false than to prove it true. Thus when we say that the null hypothesis is not rejected, we do not categorically say that it is true.

 

(Retrieved from:  http://www.scribd.com/doc/29008297/hypothesis#download, On 6th August, 2012.

(Zainul, M., (1996) A Hand Book of Research for the Fellows of M. Phil and Ph. D Programmes. Dhaka: Book Syndicate. P. 23-27)

 

9.6/C2 Application of Hypothesis in Research:

It is obviously true that hypotheses are useful and they conduct the research process in the proper direction. Decision-Makers frequently face situations in which they are interested in testing hypothesis on the basis of available information and then take decisions on the basis of such testing. In the same way a researcher takes up a research with a view to solve a particular problem. To solve the problem researcher takes the best way that is hypothesis. It is the most important tool of the research.

At the first step a researcher reads many related literatures to his/her research topic also the researcher reads through many relative theories. After reading theories or past researcher papers some research question come in front of the researcher to find out the answer or way of solution the problems, researcher try to establish a hypothesis. The researcher can also select hypothesis without basis on theory or past literature. After selecting hypothesis researcher try to establish hypothesis as theory, for this reason he/she start to collect data from relevant source.

End of the data collection researcher try to find out the validity and reliability of the hypothesis. If the hypothesis being accurate gradually it become theory, if it rejected then it lost its validity. In this way hypothesis is applied in research. The  hypothesis becomes fruitful when it becomes valid.

(Ghosh, B. N., (1992). Scientific Method and Social Research. 3rd ed. Sterling publisher pvt. Ltd. P. 55)

(Retrieved from: http://www.indiastudychannel.com/resources/99671-Hypotheses-Research.aspx, On 6th August, 2012.)

 

9.7/C2 Five Steps of Hypothesis Testing

The basic logic of hypothesis testing is to prove or disprove the research question. By only allowing an error of 5% or 1% and making correct decisions based on statistical principles, the researcher can conclude that the result must be real if chance alone could produce the same result only 5% of the time or less. These five steps consists of all the decisions a researcher needs to make in order to answer any research question using an inferential statistical test.

Meaning & Understanding

9.1/C3.1 Generalization: Generalization is the overview on something depending on some experience.

Observation: Observation is the process through which a researcher keeps looking under the respondent to know about their activities.

 

9.2/C3.1 Theory: Theory is well established facts to everyone.

Cursory: Do any work quickly

Beacon: It is one kind of light

Variable: Some thing which is changeable

9.3/C3.1 Sample: It is called the respondent of research

9.5/C3.1 Validity: Its indicate the legality

Statistical: It means mathematical

 

9.6/C3.1 Literature: Hear it indicate the past research paper

Research Question: To do research when some question come in front of researcher

Wikipedia

9.2/C3.2 Retrieved from: http://en.wikipedia.org/wiki/Hypothesis, On 11 August, 2012

9.3/C3.2 Retrieved from: http://en.wikipedia.org/wiki/Terror_management_theory#Importance_of_the_DTA_Hypothesis, On 11 August, 2012.

9.4/C3.2 Retrieved from: http://en.wikipedia.org/wiki/Null_hypothesis, On 11 August, 2012.

Retrieved from:

http://en.wikipedia.org/wiki/Alternative_hypothesis, On 11 August, 2012.

Retrieved from:

http://en.wikipedia.org/wiki/Working_hypothesis, On 11 August, 2012.

9.5/9.6/C3.2 Retrieved from: http://en.wikipedia.org/wiki/Hypothesis#Uses, On 11 August, 2012.

Retrieved from:

http://en.wikipedia.org/wiki/Statistical_hypothesis_testing, On 11 August, 2012.

YouTube

9.2/C3.3 Retrieved from: http://www.youtube.com/watch?v=k8gWymA3ZgM, On 10th August, 2012.

9.5/C3.3 Retrieved from: http://www.youtube.com/watch?v=04jnZdrcw8w, On 10th August, 2012.

Retrieved from: http://www.youtube.com/watch?NR=1&feature=endscreen&v=McISiEiXgfE, On 10th August, 2012.

Retrieved from: http://www.youtube.com/watch?v=giC6ZYBIeFY, On 10th August, 2012.

Google

9.2/C3.4 Retrieved from: http://www.indiastudychannel.com/resources/99671-Hypotheses-Research .aspx, On 6th August 2012.

Retrieved from:

http://www.socialresearchmethods.net/kb/hypothes.php, On 11th August 2012.

Retrieved from:

http://wiki.answers.com/Q/What_does_hypothesis_mean, On 11th August 2012.

9.4/C3.4 Retrieved from:

http://wiki.answers.com/Q/What_are_the_different_types_of_hypothesis, On 11th August 2012.

Retrieved from:

http://www.ehow.com/info_8659964_types-research-hypotheses.html, On 12th August 2012.

9.5/C3.4 Retrieved from: http://www.unc.edu/~jamison m/fivesteps.htm, On10th August, 2012.

Retrieved from: http://faculty.txwes.edu/mskerr/files/2420/Ch8_2420.htm, On 10th August, 2012.

Retrieved from: http://www.wadsworth.com/psychology_d/templates/student_resources/workshops/stat_workshp/hypth_test/hypth_test_06.html, On 11th August 2012.

Library & Seminar

9.2/C3.5 Zainul, M., (1996) A Hand Book of Research for the Fellows of M. Phil and Ph. D Programmes. Dhaka: Book Syndicate. P. 23-27

Galtung, J., (1980) Theory and Methods of Social Research. New Delhi: S. chand & Co. Ltd. P. 309

Raj, H., (1981) Theory and Practice in Social Research.

9.2/C3.5 Zainul, M., (1996) A Hand Book of Research for the Fellows of M. Phil and Ph. D Programmes. Dhaka: Book Syndicate. P. 23-27

Galtung, J., (1980) Theory and Methods of Social Research. New Delhi: S. chand & Co. Ltd. P. 309

Raj, H., (1981) Theory and Practice in Social Research.

 

9.4/C3.5 Good, W.J. & Hatt, P.K., (1952) Methods in Social Research. 2nd ed. NewYork: McGraw Hill Book Company, Inc. p. 59-67

Lundberg, G.A., (1968) Social Research. 2nd ed. U.S.A.: David McKay Company, Inc. p. 117

9.5/C3.5 Good, W.J. & Hatt, P.K., (1952) Methods in Social Research. 2nd ed. New York: McGraw Hill Book Company, Inc. p. 74-76

Babbie, E., (2004) The practice of Social Research, 10th ed. Asia Thomson Learning.

9.6/C3.5 Lundberg, G. A., (1968) Social Research. 2nd ed. U.S.A.: David McKay Company, Inc. p. 120

Singh, K., (2009) Qualitative Social Research Methods. New Delhi: India Pvt. Ltd. P. 154-155

9 Hypothesis

  • Ø9.1 Introduction

 

 

 

 

 

 

 

 

 

  • Ø9.2 Definition of Hypothesis

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  • Ø 9.3 Importance of Hypothesis

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  • Ø 9.4 Types of Hypothesis

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  • Ø 9.5 Procedure of Testing Hypothesis

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  • Ø 9.6 Application of Hypothesis in Research

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  • Ø 9.7 Five Steps of Hypothesis Testing

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  • Ø9.8 Introductory

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  • Ø9.8.1 Use of Hypothesis

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  • Ø9.8.2 Problems of Hypothesis

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  • Ø9.8.3 Developing an Hypothesis

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  • Ø9.9 Introduction

 

 

 

 

 

 

 

  • Ø 9.9.1 Meaning of Hypotheses

 

 

 

 

 

 

 

 

 

 

  • Ø 9.9.2 Importance of Hypotheses:

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  • Ø 9.9.3 Sources for hypotheses formulation

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  • Ø 9.10 Definition of Hypothesis

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

9.1/C2 Introduction:

A hypothesis is a tentative generalization, the validity of which has got to be tested. It is typically considered as the principal instrument in research. Its main function is to suggest new experiment and observations. Enthusiastic observation, creative thinking, feeling, unit, imagination, vision, insight and sound judgment are of greater importance in setting up reasonable hypotheses. The formulation of hypotheses plays an important part in the growth of knowledge in every science. The hypotheses are formulated to facilitate the findings of the research study.

(Ghosh, B. N., (1992). Scientific Method and Social Research. 3rd ed. Sterling publisher pvt. Ltd. P. 51-52)

 

9.2/C2 Definition of Hypothesis:

Hypothesis is considered as one of the principle instrument in research. In simplest of words, it is a general idea of the researcher that this may be perhaps the answer to a problem. Generally Hypotheses indicate any tentative solution to a problem. After the verification, when the hypothesis is

 found to be true, a theory is stabilized.

In the word of Richard D. Crisp, (1957) “A hypothesis may be defined as a tentative theory or supposition set up and adopted provisionally as a guide in the further investigation of other facts or relations.”

According to M.H. Gopal, “A hypothesis is a tentative solution posed on a cursory observation of known and available data and adopted provisionally to explain certain events and to guide in the investigation of others. It is, in fact, a possible solution to the problem.”

In the words of Van Dalen, (1956) “A hypotheses serves as a powerful beacon that lights the way for the research worker.”

From this definition we can get some characteristics of hypothesis this are given below:

v  Hypothesis should be clear and precise.

v  Hypothesis should be capable of being tested.

v  Hypothesis should state relationship between variables.

v  Hypothesis should be consisted with most known facts.

v  Hypothesis should be amenable to testing within a reasonable time.

So, we can analyze the meaning of Hypotheses as a tool of research which

tells the researcher what he has to do, how he has to do and what kind of results be expected, in context of the problem. So the research hypothesis is a predictive statement, capable of being tested by scientific methods, that relates independent variables to some dependent variable. For example, consider statements like the following ones: “Students who receive counseling will show a greater increase in creativity than students not receiving counseling.”

(Kothari, C. R., (1999) Research Methodology Methods & Technique. India: Wishwa Prakashan. P. 223-224)

 

9.3/C2 Importance of Hypothesis

Hypothesis has a great importance in research although it absorbs a very small place in the body of a research. It is almost impossible for a research worker not to have and or more hypotheses before proceeding with his work. The importance of hypothesis can be more specifically stated as under:

v  It Provides direction to research. It defines what is relevant and what is irrelevant. Thus it prevents the appraisal of irrelevant literature and the collection of useless or overload data.

v  It is the investigator’s eye- a sort of guiding light in the world of darkness.

v  It prevents blind research. Prevents haphazard gathering of data which may later turn to be irrelevant.

v  It places clear and specific goals prior to us. These clear and particular goals provide the investigator with a foundation for selecting samples and research procedures to meet these goals.

v  It directs the researcher to collect data in an orderly way.

v  It establishes the relationship between prediction and actual observation.

v  It serves the function of the linking together related facts and information and organizing to them in one comprehensible whole.

v  It enables the investigator to understand clearly with his problem and its consequences, as well as data which beat on it.

v  It serves as a formulation for drawing conclusions. It provides the outline for setting conclusions in a meaningful way.

(Zainul, M., (1996) A Hand Book of Research for the Fellows of M. Phil and Ph. D Programmes. Dhaka: Book Syndicate. P. 23-27)

(Retrieved from:  http://www.scribd.com/doc/29008297/hypothesis#download, On 6th August, 2012.

 

9.4/C2 Types of Hypothesis

Practically to conducting a research work a researcher formulates three types of hypothesis. These are:

  1.   iv.            Working Hypothesis
  2.      v.            Null Hypothesis
  3.   vi.            Alternative or Alternate Hypothesis

Frequently he begins his work with a working hypothesis. These are discussed below-

i. Working Hypothesis:

A working or trial hypothesis is provisionally adopted to explain relationship between some observed facts, for guiding a researcher in the investigation of a problem. Since a researcher, tests it in the light of gathered information/data, it is called trial or working hypothesis. In the word of Wilson Gee (1950), “A statement constitutes a trial or working hypothesis (which) is to be tested, and confirmed, modified or even abandoned as the investigation proceeds.”

Example: Child mortality rate is decreasing because of available medical facilities.

 

ii. Null Hypothesis:

A null hypothesis is formulated against the working hypothesis. So a null hypothesis is contrary to the positive statement made in the working hypothesis. Null hypothesis are formulated for testing statistical significance. When a researcher rejects a null hypothesis, he actually proves a working hypothesis. It is also easy to adapt statistical techniques to test a null hypothesis. In statistics, to mean a null hypothesis, usually ‘Ho’ is used.

For example: Ho: Child mortality rate is not decreasing because of available medical facilities.

iii. Alternate hypothesis:

It is a statement, which is accepted, after a null hypotheses is rejected based on the test result. Researcher develops such a hypothesis when he believes with adequate reasons that the alternative hypothesis explains the phenomenon most efficiently or fits the case best. The notion used to mean alternative hypothesis is ‘H1’.

For example: H1: Child mortality rate is significantly decreasing because of available medical facilities.

 

(Steven D. LeMire, S.D., (2010) An Argument Framework for the Application of Null Hypothesis Statistical Testing in Support of Research, Journal of Statistics Education, 18)

(Zainul, M., (1996) A Hand Book of Research for the Fellows of M. Phil and Ph. D Programmes. Dhaka: Book Syndicate. P. 23-27)

9.5/C2 Procedure of Testing Hypothesis

After formulating of a hypothesis, it has to be tested accurately. For testing a hypothesis, a researcher should first determine the level of significance which various between 5 percent and 1 percent. It means that the coefficient is significantly differently zero at the 1or 5 percent level. It also explains that the alternative hypothesis is acceptable at 99 or 95 percent confidence level. So, the level of significance is a line of separation between rejection and acceptance of a hypothesis. There are five steps involved in testing the reliability of hypothesis. These are briefly discussed below.

 

Step-1: Formulate a Hypothesis:

The first step is to set up two hypotheses instead of one in such that if one hypothesis is true, the other is false. Alternatively, if one hypothesis is false or rejected, the other is true or accepted. That is Ho and H1.

Step-2: Set up a Suitable Significant Level:

Having formulated the hypothesis, the next step test its validity at a certain level of significance. The assurance with which a null hypothesis rejected or accepted depends upon the significance level used for the purpose. A significance level of, say 5%, means that in the long run, the risk of making the wrong decision is about 5%. In other words, one is likely to be wrong in accepting a false hypothesis on 5 out of 100 occasions.  Significance level of, say 1% implies that there is a risk of being wrong in accepting or rejecting the hypothesis on 1 out of 100 occasions. Thus, a 1% significance level provides greater confidence to the decision than a 5% significance level.

 

Step-3: Select Test Criterion:

The third step in hypothesis testing is the selection of a suitable statistical technique as a test criterion. There are many techniques from which one is to be chosen. For example, when the hypothesis pertains to a large sample of more than 30, implying normal distribution is used. When a sample is small (less than 30), then other test will be more suitable. The test criteria that are frequently used in hypotheses testing are z, t, f & χ2.

 

Step-4: Compute:

After having selected the statistical technique to test the hypotheses accurately, the next step involves various computations for the application of that particular test. These computations include the testing statistics as its standard error.

 

Step-5: Make Decisions:

The final step in hypothesis testing is to draw a statistical decision, involving the acceptance or rejection of the null hypothesis. This will depend on whether the computed value of the test criterion falls in the region of acceptance or in the region of rejection at a given level of significance. It may be noted that the statement rejecting the hypothesis is much stronger than the statement accepting it. It is much easier to prove something false than to prove it true. Thus when we say that the null hypothesis is not rejected, we do not categorically say that it is true.

 

(Retrieved from:  http://www.scribd.com/doc/29008297/hypothesis#download, On 6th August, 2012.

(Zainul, M., (1996) A Hand Book of Research for the Fellows of M. Phil and Ph. D Programmes. Dhaka: Book Syndicate. P. 23-27)

 

9.6/C2 Application of Hypothesis in Research:

It is obviously true that hypotheses are useful and they conduct the research process in the proper direction. Decision-Makers frequently face situations in which they are interested in testing hypothesis on the basis of available information and then take decisions on the basis of such testing. In the same way a researcher takes up a research with a view to solve a particular problem. To solve the problem researcher takes the best way that is hypothesis. It is the most important tool of the research.

At the first step a researcher reads many related literatures to his/her research topic also the researcher reads through many relative theories. After reading theories or past researcher papers some research question come in front of the researcher to find out the answer or way of solution the problems, researcher try to establish a hypothesis. The researcher can also select hypothesis without basis on theory or past literature. After selecting hypothesis researcher try to establish hypothesis as theory, for this reason he/she start to collect data from relevant source.

End of the data collection researcher try to find out the validity and reliability of the hypothesis. If the hypothesis being accurate gradually it become theory, if it rejected then it lost its validity. In this way hypothesis is applied in research. The  hypothesis becomes fruitful when it becomes valid.

(Ghosh, B. N., (1992). Scientific Method and Social Research. 3rd ed. Sterling publisher pvt. Ltd. P. 55)

(Retrieved from: http://www.indiastudychannel.com/resources/99671-Hypotheses-Research.aspx, On 6th August, 2012.)

 

9.7/C2 Five Steps of Hypothesis Testing

The basic logic of hypothesis testing is to prove or disprove the research question. By only allowing an error of 5% or 1% and making correct decisions based on statistical principles, the researcher can conclude that the result must be real if chance alone could produce the same result only 5% of the time or less. These five steps consists of all the decisions a researcher needs to make in order to answer any research question using an inferential statistical test.

1. STATING THE RESEARCH QUESTION.

The first step is to state the research problem in terms of a question that identifies the population(s) of interest to the researcher, the parameter(s) of the variable under investigation, and the hypothesized value of the parameter(s). This step makes the researcher not only define what is to be tested but what variable will be used in sample data collection. The type of variable (or combination of variables as in relationship type research questions) whether categorical, discrete or continuous further defines the statistical test which can be performed on the collected data set.

For example:

Is the mean first salary of a newly graduated student equal to $30,000?

The population of interest is all students who have just graduated. The parameter of interest is the mean and the variable salary is continuous. The hypothesized value of the parameter, the mean, is $30,000. Since the parameter is a population mean of a continuous variable variable, this suggests a one sample test of a mean.


2. SPECIFY THE NULL AND ALTERNATIVE HYPOTHESES.

The second step is to state the research question in terms of a null hypothesis (H0) and a alternative hypothesis (HA). The null hypothesis is the population parameter, μ = $30,000 (H0: μ = $30,000). The alternative hypothesis is the population parameter does not equal $30,000 ( HA: μ NE $30,000). This HA suggests a two-tailed test as NE $30,000 can be less than $30,000 or more than $30,000. Sometimes the alternative hypothesis is stated in terms of a direction such as less than or greater than a value such at

$30,000. A directional HA calls for a one-tailed test, in the direction stated in the HA.

The next part of step 2 is to select a significance level (Type I error) typically alpha is used at the .05 or the .01 level. A good researcher will also not neglect Type II error. In this step we are not only setting up our research question in terms of statistical hypotheses, but we must evaluate whether all the assumptions appropriate for the statistical test have been met.

Example:

H0: μ = $30,000

HA: μ NE $30,000 alpha=.05

Test assumptions are 1) the population is normally distributed or sample size is approximately >=30 and 2)

the sample we have used to collect the data was drawn randomly from the population. If these test

assumptions have not been meet, then data collection should be reevaluated or continued under caution.


3. CALCULATE TEST STATISTIC.

The third step is to calculate a statistic analogous to the parameter specified by the null hypothesis. If the null hypothesis is defined by the parameter μ, then the statistics computed on our data set would be the mean (xbar) and the standard deviation (s). A histogram of our sample data set gives us our best approximation of what we expect our population distribution to look like.

Since the best estimate of μ is xbar, our sample mean, the test statistic is based on a distribution of sample means, the sampling distribution of the mean, xbar, with n, sample size, equal to the number of data values used to compute xbar. We have hypothesized from the research question the mean of this distribution and want to see if our sample mean is close to this value.

To determine where our sample mean fits on this sampling distribution, we convert our sample mean, xbar, to a z-score. Thus the test statistic would be :

z = xbar-μ (hypothesized) standard error of xbar The standard error of xbar (point estimate) is s, the sample standard deviation, divided by square root of n, the sample size since the population standard deviation is unknown.

Example:

Suppose we randomly sampled 100 high school seniors and determined their salary of their first job. The sample mean salary, xbar, was $29,000 with a standard deviation of $6,000. Since sample size is >30, we don’t have to worry about whether the population is normally distributed (Central Limit Theorem). The test statistic would be:

z = $29,000 – $30,000 = -$1,000 = -1.667

$6,000/sqrt(100) $600


 

4. COMPUTE PROBABILITY OF TEST STATISTIC OR REJECTION REGION.

The fourth step is to calculate the probability value (often called the p-value) which is the probability of the test statistic for both tails since this this two-

tailed test. The probability value computed in this step is compared with the significance level selected in step 2. If the probability is less than or equal to the significance level, then the null hypothesis is rejected. If the probability is greater than the significance level then the null hypothesis is not rejected. When the null hypothesis is rejected, the outcome is said to be “statistically significant”; when the null hypothesis is not rejected then the outcome is said be “not statistically significant.” If the outcome is statistically significant, then the null hypothesis is rejected in favor of the alternative hypothesis.

Example:

 

P(z> 1.667) =.048 + P(z< –1.667)=.048, the p-value is .048+.048=.096 Since this value is greater than alpha=.05 selected when we set up out hypotheses, we accept the null hypothesis, H0: μ = $30,000.

If we wish to use a rejection region of alpha=.05 (.025 in each tail) to determine if we accept or reject the null hypothesis, the cut-off z-score would be -1.96 and 1.96. If our test statistic is >=1.96 or <= -1.96, then we would reject the null hypothesis at alpha=.05. We can say that our test statistic (transformed into a z-score) is in the rejection region. In this example, our test statistic, z=-1.667 for our test statistic does not fall in the rejection region (sometimes called the acceptance region), so we must accept the null hypothesis.

5. STATE CONCLUSIONS.

The fifth and final step is to describe the results and state correct statistical conclusions in an understandable way. The conclusions consists of two statments-one describing the results of the null hypothesis and the other describing the results of the alternative hypothesis. The first statement should state as to whether we accepted or rejected the null hypothesis and for what value of alpha or p-value for our test statistic. The second statement should answer the research question proposed in step 1 stating the sample statistic collected which estimated the parameter we hypothesized.

 

Example:

Accept the null hypothesis at alpha=.05 or p-value of .096. Based on a sample mean of $25,000, the mean

salary of a newly graduated student does not equal $30,000.

(http://www.unc.edu/~jamisonm/fivesteps.htm , On 06 November, 2012.)

9.8/C2 Hypothesis:

A hypothesis (fromGreek plural hypotheses) is a proposed explanation for an observable phenomenon. The term derives from the Greek hypotithenai meaning “to put under” or “to suppose.” For a hypothesis to be put forward as a scientific hypothesis, the scientific method requires that one can test it. Scientists generally base scientific hypotheses on previous observations that cannot be satisfactorily explained with the available scientific theories.  Even though the words “hypothesis” and “theory” are often used synonymously in common and informal usage, a scientific hypothesis is not the same as a scientific theory although the difference is sometimes more one of degree than of principle.

A working hypothesis is a provisionally accepted hypothesis. In a related but distinguishable usage, the term hypothesis is used for the antecedent of a proposition; thus in proposition “If P, then Q”, P denotes the hypothesis (or antecedent); Q can be called a consequent. P is the assumption in a (possibly counterfactual) What If question. The adjective hypothetical, meaning “having the nature of a hypothesis”, or “being assumed to exist as an immediate consequence of a hypothesis”, can refer to any of these meanings of the term “hypothesis”.

9.8.1/C2 Uses:

In Plato’s Meno(86e-87b),Socrates dissects virtue with a method used by mathematicians, that of ‘investigating from a hypothesis’. In this sense, ‘hypothesis’ refers to a clever idea or to a convenient mathematical approach that simplifies cumbers some calculations. Cardinal Bellarmine gave a famous example of this usage in the warning issued to Galileoin the early 17th century: that he must not treat the motion of the Earth as a reality, but merely as a hypothesis.

In common usage in the 21st century, a hypothesis refers to a provisional idea whose merit requires evaluation. For proper evaluation, the framer of a hypothesis needs to define specifics in operational terms. A hypothesis requires more work by the researcher in order to either confirm or disprove it. In due course, a confirmed hypothesis may become part of a theory or occasionally may grow to become a theory itself. Normally, scientific hypotheses have the form of a mathematical model. Sometimes, but not always, one can also formulate them as existential statements, stating that some particular instance of the phenomenon under examination has some characteristic and causal explanations, which have the general form of universal statements, stating that every instance of the phenomenon has a particular characteristic.

Any useful hypothesis will enable predictions by reasoning (including deductive reasoning). It might predict the outcome of an experiment in a laboratory setting or the observation of a phenomenon in nature. The prediction may also invoke statistics and only talk about probabilities. Karl Popper, following others, has argued that a hypothesis must be falsifiable, and that one cannot regard a proposition or theory as scientific if it does not admit the possibility of being shown false.

Other philosophers of science have rejected the criterion of falsifiability or supplemented it with other criteria, such as verifiability (e.g., verificationism) or coherence (e.g., confirmation holism). The scientific method involves experimentation on the basis of hypotheses in order to answer questions and explore observations. In framing a hypothesis, the investigator must not currently know the outcome of a test or that it remains reasonably under continuing investigation. Only in such cases does the experiment, test or study potentially increase the probability of showing the truth of a hypothesis. If the researcher already knows the outcome, it counts as a “consequence”

And the researcher should have already considered this while formulating the hypothesis. If one cannot assess the predictions by observation or by experience, the hypothesis classes as not yet useful, and must wait for others who might come afterward to make possible the needed observations. For example, a new technology or theory might make the necessary experiments feasible.

Scientific hypothesis

People refer to a trial solution to a problem as a hypothesis often called an “educatedguess” because it provides a suggested solution based on the evidence. Experimenters may test and reject several hypotheses before solving the problem.

According to Schick and Vaughn, researchers weighing up alternative hypotheses may take into consideration:

  • Testability- (compare falsifiability as discussed above)
  • Simplicity- (as in the application of “Occam’s razor”, discouraging the postulation- of excessive numbers of entities)
  • Scope- the apparent application of the hypothesis to multiple cases of phenomena
  • Fruitfulness- the prospect that a hypothesis may explain further phenomena in the future
  • Conservatism- the degree of “fit” with existing recognized knowledge systems

Evaluating hypotheses

According to Karl Popper’s hypothetico-deductive method (also known as the method of “conjecture sand refutations”) demands falsifiable hypotheses, framed in such a manner that the scientific community can prove them false (usually by observation). According to this view, a hypothesis cannot be “confirmed”, because there is always the possibility that a future experiment will show that it is false. Hence, failing to falsify a hypothesis does not prove that hypothesis: it remains provisional.

However, a hypothesis that has been rigorously tested and not falsified can form a reasonable basis for action, i.e., we can act as if it is true, until such time as it is falsified. Just because we’ve never observed rain falling upward, doesn’t mean that we never will however improbable, our theory of gravity may be falsified some day. Popper’s view is not the only view on evaluating hypotheses. For example, some forms of empiricism hold that under a well-crafted, well-controlled experiment, a lack of falsification does count as verification, since such an experiment ranges over the full scope of possibilities in the problem domain.

Should we ever discover some place where gravity did not function, and rain fell upward, this would not falsify our current theory of gravity (which, on this view, has been verified by innumerable well-formed experiments in the past) it would rather suggest an expansion of our theory to encompass some new force or previously undiscoverd interaction of forces. In other words, our initial theory as it stands is verified but incomplete. This situation illustrates the importance of having well-crafted, well-controlled experiments that range over the full scope of possibilities for applying the theory. In recent years philosophers of science have tried to integrate the various approaches to evaluating hypothesis and the scientific method in general, to form a more complete system that integrates the individual concerns of each approach. Notably, Imre LakatosandPaul Feyerabend, both former students of Popper, have produced novel attempts at such a synthesis.

Statistical hypothesis testing:

Statistical hypothesis testing When a possible correlation or similar relation between phenomena is investigated, such as, for example, whether a proposed remedy is effective in treating a disease, that is, at least to some extent and for some patients, the hypothesis that a relation exists cannot be examined the same way one might examine a proposed new law of nature: in such an investigation a few cases in which the tested remedy shows no effect do not falsify the hypothesis. Instead, statistical tests are used to determine how likely it is that the overall effect would be observed if no real relation as hypothesized exists.

If that likelihood is sufficiently small (e.g., less than1%), the existence of a relation may be assumed. Otherwise, any observed effect may as well be due to pure chance. In statistical hypothesis testing two hypotheses are compared, which are called the null hypothesis and the alternative hypothesis. The null hypothesis is the hypothesis that states that there is no relation between the phenomena whose relation is under investigation, or at least not of the form given by the alternative hypothesis. The alternative hypothesis, as the name suggests, is the alternative to the null hypothesis: it states that there is some kind of relation. The alternative hypothesis may take several forms, depending on the nature of the hypothesized relation; in particular, it can be two-sided (for example: there is some effect, in a yet unknown direction) or one-sided (the direction of the hypothesized relation, positive or negative, is fixed in advance).Proper use of statistical testing requires that these hypotheses, and the threshold (such as 1%)at which the null hypothesis is rejected and the alternative hypothesis is accepted, all be determined in advance, before the observations are collected or inspected. If these criteria are determined later, when the data to be tested is already known, the test is invalid.

9.8.2/C2 Problem:

Inferential Statistics – Testing of hypothesis using five step procedure

1. The new director of special programs in XYZ Corporation felt the customers were waiting too long to receive and complete forms needed to enroll in special programs. After collecting some data, Ms. Jones determined the mean wait time was 28 minutes. She felt this time period was excessive and she instituted new procedures to streamline the process. One month later, a sample of 127 customers was selected. The mean wait time recorded was 26.9 minutes and the standard deviation of the sampling was 8 minutes. Using the 0.02 level of significance, conduct a five-step hypothesis testing procedure to determine if the new processes significantly reduced the wait time.

2. A study was conducted on the annual incomes of corporate trainers in the state of New York in metropolitan areas having a population less than 100,000 and in metropolitan are as having a population over 500,000. Some sample statistics are: SAMPLE STATISTIC POPULATION LESS THAN 100K POPULATION MORE THAN500K Sample Size 45,60 Sample Mean $31,290,$31,330 Sample SD $1,060 ,$1,900Test the hypothesis that the annual income of corporate trainers in areas of more then500,000 are significantly more than those in areas of less than 100,000. Use the 5% level of risk.

3. In a recent national survey, the mean weekly allowance for a nine-year-old child from his or her parents was reported to be $3.65. A random sample of 45 nine-year-olds in northwestern Ohio revealed the mean allowance to be $3.69 with a standard deviation of 0.24. At the 0.05 level of significance, is there a difference in the mean allowances nationally and the mean allowances in northwestern Ohio for nine-year-olds?

4. Metro Real Estate Association is preparing a pamphlet that they feel might be of interest to prospective homebuyers in the Middletown and Brockton areas of the city. One item of interest is the number of years children remain in the same district for schooling. A sample of 40 households with school-aged children in Middletown was randomly selected. The mean length of time in the district was 7.6 years, with a standard deviation of 2.3 years. A sample of 55 households in Brockton revealed the mean length of time in the district was 8.1 years, with a standard deviation of 2.9 years. At the 0.05 level of significance, can we conclude the Middletown students stayed in their districts less time than the Brockton students? Use the five-step hypothesis testing procedure.

5. A sample of 40 observations is selected from one somewhat normal population. The sample mean is 102 and the sample standard deviation is 5. A sample of 50 observations isselected from a second source. The sample mean was 99 and the standard deviation was 6.Conduct a test of the hypothesis using the 0.04 level of significance.

 

9.8.3/C2 Developing an Hypothesis Statement:

Whenever an experiment is conducted, the scientist performing the experiment must know what he is trying to prove. Actually, scientists rarely prove anything. Normally, they “support” or “reject” their hypothesis. In this exercise you will have the chance to develop several hypothesis that might be tested in a laboratory. Note: you will not necessarily test any of your hypothesis, but each one must be TESTABLE. (just in case)Below is a list of “observations” made by someone such as yourself. Based on the observations, develop a workable hypothesis that could be used to test some aspect of the observation. Remember, an HYPOTHESIS is an EDUCATED GUESS that is TESTABLE. You must use complete sentences.

List of Observations:

1. Bees spend hours flying around the paperboy when he wears his bright yellow “highly visible” vests, but not on days when he does not wear the vest.

 2. Shiny nail rust when left exposed on a construction site, but galvanized nails do not rust in the same condition.

 3. Kim notices that Brad’s Brown Bread does not mold after a week in an open bag. Walter’s Wonderful White Bread grows a layer of black fur in the same length of time in it’s open bag.

 4. Sam, an avid lizard lover, has a hard time catching up with the wild lizards during the summer. His luck changes when the cool days of November arrive,

 5. Perry’s Porsche won’t start.

 6. While camping, Terry refuses to bathe, think it unmanly. Jeff takes at least a sponge bath every other day. After two weeks, Jeff is covered with mosquito bites. Terry is virtually bite free.

7. A boat owner complains about having to scrape barnacles from the hull of his sailboat that is docked in San Diego Bay. he says he never has to scrape them from his houseboat in Lake Shasta.

 8. After playing basketball, Mr. Christensen sweats terribly, turns red, and looks as though he’s going to pass out. He complains that he never used to feel this way after a game.

The Development Hypothesis (1852)

Herbert Spencer:

This early essay of Spencer’s was originally published anonymously in The Leader for March20 1852. It was the second contribution in a regular series entitled “The Haythorne Papers”. Spencer’s identity was revealed some while after. It is reproduced in Herbert Spencer, Essays Scientific, Political & Speculative, Williams and Norgate (3 vols 1891) pp.1-7]; and here in full. David Clifford, Ph.D., Cambridge University, prepared the html text in 1997; George P.Landow reformatted it in 2008.Joachim Dagg, Abteilungfür Entomologie, Institutfür Phytopathologie und Pflanzenschutz, Göttingen, has written to point out that ‘the version Spencer later published differs from the original in The Leader of 20 March 1852 in one crucial phrase: “Those who cavalierly reject the Theory of Evolution…” originally read “Those who cavalierly reject the Theory of Lamarck…”In a debate upon the development hypothesis, lately narrated to me by a friend, one of the disputants was described as arguing that as, in all our experience, we know no such phenomenon as transmutation of species, it is unphilosophical to assume that transmutation of species ever takes place. Had I been present I think that passing over his assertion, which is open to criticism, I should have replied that as in all our experience we have never known a species created, it was, by his own showing, unphilosophical to assume that any species ever had been created.

Those who cavalierly reject the Theory of Evolution as not being adequately supported by facts seem to forget that their own theory is supported by no facts at all. Like the majority of men who are born to a given belief, they demand the most rigorous proof of any adverse belief, but assume that their own needs none. Here we find, scattered over the globe, vegetable and animal organisms numbering, of the one kind (according to Humboldt), some320,000 species, and of the other, some 2,000,000 species (see Carpenter) and if to these we add the numbers of animal and vegetable species which have become extinct, we may safely estimate the number of species that have existed, and are existing, on the Earth, at not less than ten millions. Well, which is the most rational theory about these ten millions of species? Is it most likely that there have been ten millions of special creations? Or is it most likely that, by continual modifications due to change of circumstances, ten millions of varieties have been produced, as varieties are being produced still? Doubtless many will reply that they can more easily conceive ten millions of special creations to have taken place, than they can conceive that ten millions of varieties have arisen by successive modifications. All such, however, will find, on inquiry, that they are under a nillusion.

This is one of the many cases in which men do not really believe, but rather believe they believe. It is not that they can truly conceive ten millions of special creations to have taken place, but that they think they can do so. Careful introspection will show them that they have never yet realized to themselves the creation of even one species If they have formed a definite conception of the process, let them tell us how a new species is constructed, and how it makes its appearance. Is it thrown down from the clouds? or must we hold to the notion that it struggles up out of the ground?

Do its limbs and viscera rush together from all the points of the compass? Or must we receive the old Hebrew idea, that God takes clay and moulds a new creature? If they say that a new creature is produced in none of these modes, which are too absurd to be believed, then they are required to describe the mode in which anew creature may be produced – a mode which does not seem absurd; and such a mode they will find that they neither have conceived nor can conceive. Should the believers in special creations consider it unfair thus to call upon them to describe how special creations take place, I reply that this is far less than they demand from the supporters of the Development Hypothesis.

They are merely asked to point out a conceivable mode. On the other hand, they ask, not simply for a conceivable mode, but for the actual mode. They do not say – Show us how this may take place; but they say – Show us how this does take place. So far from its being unreasonable to put the above question, it would be reasonable to ask not only for a possible mode of special creation, but for an ascertained mode; seeing that this is no greater a demand than they make upon their opponents. And here we may perceive how much more defensible the new doctrine is than the old one. Even could the supporters of the Development Hypothesis merely show that the origination of species by the process of modification is conceivable, they would be in a better position than their opponents. But they can do much more than this.

They can show that the process of modification has effected, and is effecting, decided changes in all organisms subject to modifying influences. Though, from the impossibility of getting at a sufficiency of facts, they are unable to trace the many phases through which any existing species has passed in arriving at its present form, or to identify the influences which caused the successive modifications; yet, they can show that any existing species – animal or vegetable – when placed under conditions different from its previous ones, immediately begins to undergo certain changes fitting it for the new conditions.

They can show that in successive generations these changes continue; until, ultimately, the new conditions become the natural ones. They can show that in cultivated plants, in domesticated animals, and in the several races of men, such alterations have taken place. They can show that the degrees of difference so produced are often, as in dogs, greater than those on which distinctions of species are in other cases founded. They can show that it is a matter of dispute whether some of these modified forms are varieties or separate species. They can show, too, that the changes daily taking place in ourselves – the facility that attends long practice, and the loss of aptitude that begins when practice ceases -the strengthening of passions habitually gratified, and the weakening of those habitually curbed – the development of every faculty, bodily, moral, or intellectual, according to the use made of it – are all explicable on this same principle.

And thus they can show that throughout all organic nature there is at work a modifying influence of the kind they assign as the cause of these specific differences an influence which, though slow in its action, does, in time, if the circumstances demand it, produce marked changes – an influence which, to all appearance, would produce in the millions of years, and under the great varieties of condition which geological records imply, any amount of change. Which, then, is the most rational hypothesis? – that of special creations which has neither a fact to support it nor is even definitely conceivable; or that of modification, which is not only definitely conceivable, but is countenanced by the habitudes of every existing organism?

That by any series of changes a protozoon should ever become a mammal, seems to those who are not familiar with zoology, and who have not seen how clear becomes the relationship between the simplest and the most complex forms when intermediate forms are examined, a very grotesque notion. Habitually looking at things rather in their statical aspect than in their dynamical aspect they never realize the fact that, by small increments of modification, any amount of modification may in time be generated. That surprise which they feel on finding one whom they last saw as a boy, grown into a man, becomes incredulity when the degree of change is greater. Nevertheless, abundant instances are at hand of the mode in which we may pass to the most diverse forms by insensible gradations. Arguing the matter some time since with a learned professor, I illustrated my position thus:-You admit that there is no apparent relationship between a circle and an hyperbola. The one is a finite curve; the other is an infinite one. All parts of the one are alike; of the other no parts are alike [save parts on its opposite sides]. The one in closes a space; the other will not in close a space though produced for ever. Yet opposite as are these curves in all their properties, they may be connected together by a series of intermediate curves, no one of which differs from the adjacent ones in any appreciable degree. Thus, if a cone be cut by a plane at right angles to its axis we get a circle.

If, instead of being perfectly at right angles, the plane subtends with the axis an angle of 89° 59′, we have an ellipse which no human eye, even when aided by an accurate pair of compasses, can distinguish from a circle. Decreasing the angle minute by minute, the ellipse becomes first perceptibly eccentric, then manifestly so, and by and by acquires so immensely elongated a form, as to bear no recognizable resemblance to a circle. By continuing this process, the ellipse passes insensibly into a parabola; and, ultimately, by still further diminishing the angle, into an hyperbola.

Now here we have four different species of curve-circle, ellipse, parabola, and hyperbola – each having its peculiar properties and its separate equation, and the first and last of which are quite opposite in nature, connected together as members of one series, all producible by a single process of insensible modification. But the blindness of those who think it absurd to suppose that complex organic forms may have arisen by successive modifications out of simple ones, becomes astonishing when were member that complex organic forms arc daily being thus produced. A tree differs from a seed immeasurably in every respect – in bulk, in structure, in colour, in form, in chemical composition: differs so greatly that no visible resemblance of any kind can be pointed out between them. Yet is the one changed in the course of a few years into the other changed so gradually, that at no moment can it be said – Now the seed ceases to he, and the tree exists. What can be more widely contrasted than a newly-born child and the small, semi-transparentsphe rule constituting the human ovum? The infant is so complex in structure that a cyclopedia is needed to describe its constituent parts. The germinal vesicle is so simple that it may be defined in a line. Nevertheless a few months suffice to develop the one out of the other; and that, too, by a series of modifications so small, that were the embryo examined at successive minutes, even a microscope would with difficulty disclose any sensible changes.

That the uneducated and the ill-educated should think the hypothesis that all races of beings, man inclusive, may in process of time have been evolved from the simplest monad, aludicrous one, is not to be wondered at. But for the physiologist, who knows that every individual being is so evolved – who knows, further, that in their earliest condition the germs of all plants and animals whatever are so similar, “that there is no appreciable distinction amongst them, which would enable it to be determined whether a particular molecule is the germ of a Conferva or of an Oak, of a Zoophyte or of a Man;” [Carpenter, Principles of Comparative Physiology, p.474.] – for him to make a difficulty of the matter is in excusable.

Surely if a single cell may, when subjected to certain influences, become a man in the space of twenty years; there is nothing absurd in the hypothesis that under certain other influences, a cell may, in the course of millions of years, give origin to the human race. We have, indeed, in the part taken by many scientific men in this controversy of “Law versus Miracle,” a good illustration of the tenacious vitality of superstitions. Ask one of our leading geologists or physiologists whether he believes in the Mosaic account of the creation, and he will take the question as next to an insult. Either he rejects the narrative entirely, or under stands it in some vague non- natural sense. Yet no part of it he unconsciously adopts; and that, too, literally. For whence has he got this notion of “special creations,” which he thinks so reasonable, and fights for so vigorously? Evidently he can trace it back to no other source than this myth which be repudiates.

He has not a single fact in nature to cite in proof of it; nor is ho prepared with any chain of reasoning by which it may be established. Catechize him, and he will be forced to confess that the notion was put into his mind in childhood as part or a story which he now thinks absurd. And why, after rejecting all the rest of the story, he should strenuously defend this last remnant of it, as though he had received it on valid authority, he would be puzzled to say.

(http://www.scribd.com/doc/26542110/Assignment-on-Hypothesis, 6th November, 2012)

9.9/C2Introduction:
A researcher takes up a research with a view to solve a particular problem. When the researcher looks into the direction of solving a problem he finds not one but many ways to reach the solution of a problem.
Now if he tries each of the possible direction to make out which would be the best to solve a problem, then there would be a lot of wastage of time as well as effort. To avoid this trial and error method, the researcher simply analyses all the possible ways and derives the best one of them, the best and theoretical sound alternative. This sound alternative is nothing else but the Hypotheses of research. It is the most important tool of the research.

9.9.1/C2 Meaning of Hypotheses:
We generally define the Hypotheses as a tentative solution to a problem. In simplest of words, it is a general idea of the researcher that this may be perhaps the answer to a problem.
In the words of Van Dalen, (1956) “A hypotheses serves as a powerful beacon that lights the way for the research worker.”
So, we can analyze the meaning of Hypotheses as a tool of research which tells the researcher what he has to do, how he has to do and what kind of results be expected thereon, in context of the problem.
So it is understood that the hypotheses is a sheer guess, a hunch or a simple supposition in the direction of finding an answer to the question, or solution to the problem.

9.9.2/C2 Importance of Hypotheses:

A hypothesis is referred to as a very important tool in research. It serves the following purposes:

• It provides a direction to the research and prevents waste of time and effort of the researcher.
• It sets a limit to the researcher’s point of view.
• It helps the researcher to look into a particular aspect of the problem

 thereby offering certain issues and facts.
• Provides the methods to be used in solving the problem
• Acts as a framework for analysis and interpretation of the data to draw conclusions.
• Suggests the areas of importance which need more attention or more collection of facts by the researcher.

Thus a hypotheses is a very important tool in a research study, hence all researches need to have a hypotheses irrespective of the kind or nature of the study. However it should not be thought that a research cannot be conducted at all without creation of hypotheses. There are many descriptive as well as historical researches that have been conducted without hypotheses. But certainly a research can be more productive and accurate in terms of results if a researcher forms hypotheses before proceeding with his research work.

 

9.9.3C2 The Sources for hypotheses formulation:

1. Background Knowledge: The researcher must go through and collect all

 information related to his problem of research by consulting already established facts, theories and other forms of related literature. This kind of background knowledge helps the researcher in understanding the important aspects of the problem, as may have taken up by previous researchers with clues for solution.

2. Experience: A researcher may get enough insight to the problem by his own experiences also. He may have a general understanding of an existing problem, its probable causes and also the solutions. Such experiences may help him to make a considerable review or analysis of the problem.

3. Analogies: The researcher may also analyze two similar situations or events or reasons for a particular problem. In this case a researcher himself makes an argument about the two situations and come to a decision.

4. Scientific Theories: Various scientific theories developed in the field of psychology, sociology, education, or any other subject may also provide the researcher the clarification regarding the direction towards his research.

Summary
In the above discussion it is made very clear that a hypothesis is not a need must a necessary tool of the research. It is of immense help to the researcher as it helps him in finding out the most suitable course of action from among many. The various sources for formulation of an effective hypothesis have also been discussed. As a matter of fact, the researcher may adopt any of the sources to formulate a meaningful hypothesis for his study, but it is essential to discuss the basis of such a hypothesis whether it is analogical argument or previous studies or his own able experience. He must declare evidently what made him formulate a certain kind of hypotheses, and then only his study will be meaningful.

http://www.indiastudychannel.com/resources/99671-Hypotheses-Research%20.aspx, On 6th August 2012)

9.10/C2 Hypotheses

An hypothesis is a specific statement of prediction. It describes in concrete (rather than theoretical) terms what you expect will happen in your study. Not all studies have hypotheses. Sometimes a study is designed to be exploratory (see inductive research). There is no formal hypothesis, and perhaps the purpose of the study is to explore some area more thoroughly in order to develop some specific hypothesis or prediction that can be tested in future research. A single study may have one or many hypotheses.

Actually, whenever I talk about an hypothesis, I am really thinking simultaneously about two hypotheses. Let’s say that you predict that there will be a relationship between two variables in your study. The way we would formally set up the hypothesis test is to formulate two hypothesis statements, one that describes your prediction and one that describes all the other possible outcomes with respect to the hypothesized relationship. Your prediction is that variable A and variable B will be related (you don’t care whether it’s a positive or negative relationship). Then the only other possible outcome would be that variable A and variable B are not related. Usually, we call the hypothesis that you support (your prediction) the alternative hypothesis, and we call the hypothesis that describes the remaining possible outcomes the null hypothesis. Sometimes we use a notation like HA or H1 to represent the alternative hypothesis or your prediction, and HO or H0 to represent the null case. You have to be careful here, though. In some studies, your prediction might very well be that there will be no difference or change. In this case, you are essentially trying to find support for the null hypothesis and you are opposed to the alternative.

If your prediction specifies a direction, and the null therefore is the no difference prediction and the prediction of the opposite direction, we call this a one-tailed hypothesis. For instance, let’s imagine that you are investigating the effects of a new employee training program and that you believe one of the outcomes will be that there will be less employee absenteeism. Your two hypotheses might be stated something like this:

The null hypothesis for this study is:

HO: As a result of the XYZ company employee training program, there will either be no significant difference in employee absenteeism or there will be a significant increase.

which is tested against the alternative hypothesis:

HA: As a result of the XYZ company employee training program, there will be a significant decrease in employee absenteeism.

In the figure on the left, we see this situation illustrated graphically. The alternative hypothesis — your prediction that the program will decrease absenteeism — is shown there. The null must account for the other two possible conditions: no difference, or an increase in absenteeism. The figure shows a hypothetical distribution of absenteeism differences. We can see that the term “one-tailed” refers to the tail of the distribution on the outcome variable.

When your prediction does not specify a direction, we say you have a two-tailed hypothesis. For instance, let’s assume you are studying a new drug treatment for depression. The drug has gone through some initial animal trials, but has not yet been tested on humans. You believe (based on theory and the previous research) that the drug will have an effect, but you are not confident enough to hypothesize a direction and say the drug will reduce depression (after all, you’ve seen more than enough promising drug treatments come along that eventually were shown to have severe side effects that actually worsened symptoms). In this case, you might state the two hypotheses like this:

The null hypothesis for this study is:

HO: As a result of 300mg./day of the ABC drug, there will be no significant difference in depression.

which is tested against the alternative hypothesis:

HA: As a result of 300mg./day of the ABC drug, there will be a significant difference in depression.

The figure on the right illustrates this two-tailed prediction for this case. Again, notice that the term “two-tailed” refers to the tails of the distribution for your outcome variable.

The important thing to remember about stating hypotheses is that you formulate your prediction (directional or not), and then you formulate a second hypothesis that is mutually exclusive of the first and incorporates all possible alternative outcomes for that case. When your study analysis is completed, the idea is that you will have to choose between the two hypotheses. If your prediction was correct, then you would (usually) reject the null hypothesis and accept the alternative. If your original prediction was not supported in the data, then you will accept the null hypothesis and reject the alternative. The logic of hypothesis testing is based on these two basic principles:

  • the formulation of two mutually exclusive hypothesis statements that, together, exhaust all possible outcomes
  • the testing of these so that one is necessarily accepted and the other rejected

OK, I know it’s a convoluted, awkward and formalistic way to ask research questions. But it encompasses a long tradition in statistics called the hypothetical-deductive model, and sometimes we just have to do things because they’re traditions. And anyway, if all of this hypothesis testing was easy enough so anybody could understand it, how do you think statisticians would stay employed?

(http://www.socialresearchmethods.net/kb/hypothes.php, On 11th August 2012)

Meaning & Understanding

9.1/C3.1 Generalization: Generalization is the overview on something depending on some experience.

Observation: Observation is the process through which a researcher keeps looking under the respondent to know about their activities.

 

9.2/C3.1 Theory: Theory is well established facts to everyone.

Cursory: Do any work quickly

Beacon: It is one kind of light

Variable: Some thing which is changeable

9.3/C3.1 Sample: It is called the respondent of research

9.5/C3.1 Validity: Its indicate the legality

Statistical: It means mathematical

 

9.6/C3.1 Literature: Hear it indicate the past research paper

Research Question: To do research when some question come in front of researcher

Wikipedia

9.2/C3.2 Retrieved from: http://en.wikipedia.org/wiki/Hypothesis, On 11 August, 2012.

9.3/C3.2 Retrieved from: http://en.wikipedia.org/wiki/Terror_management_theory#Importance_of_the_DTA_Hypothesis, On 11 August, 2012.

9.4/C3.2 Retrieved from: http://en.wikipedia.org/wiki/Null_hypothesis, On 11 August, 2012.

Retrieved from:

http://en.wikipedia.org/wiki/Alternative_hypothesis, On 11 August, 2012.

Retrieved from:

http://en.wikipedia.org/wiki/Working_hypothesis, On 11 August, 2012.

9.5/9.6/C3.2 Retrieved from: http://en.wikipedia.org/wiki/Hypothesis#Uses, On 11 August, 2012.

Retrieved from:

http://en.wikipedia.org/wiki/Statistical_hypothesis_testing, On 11 August, 2012.

YouTube

9.2/C3.3 Retrieved from: http://www.youtube.com/watch?v=k8gWymA3ZgM, On 10th August, 2012.

9.5/C3.3 Retrieved from: http://www.youtube.com/watch?v=04jnZdrcw8w, On 10th August, 2012.

Retrieved from: http://www.youtube.com/watch?NR=1&feature=endscreen&v=McISiEiXgfE, On 10th August, 2012.

Retrieved from: http://www.youtube.com/watch?v=giC6ZYBIeFY, On 10th August, 2012.

Google

9.2/C3.4 Retrieved from: http://www.indiastudychannel.com/resources/99671-Hypotheses-Research .aspx, On 6th August 2012.

Retrieved from:

http://www.socialresearchmethods.net/kb/hypothes.php, On 11th August 2012.

Retrieved from:

http://wiki.answers.com/Q/What_does_hypothesis_mean, On 11th August 2012.

9.4/C3.4 Retrieved from:

http://wiki.answers.com/Q/What_are_the_different_types_of_hypothesis, On 11th August 2012.

Retrieved from:

http://www.ehow.com/info_8659964_types-research-hypotheses.html, On 12th August 2012.

9.5/C3.4 Retrieved from: http://www.unc.edu/~jamison m/fivesteps.htm, On 10th August, 2012.

Retrieved from: http://faculty.txwes.edu/mskerr/files/2420/Ch8_2420.htm, On 10th August, 2012.

Retrieved from: http://www.wadsworth.com/psychology_d/templates/student_resources/workshops/stat_workshp/hypth_test/hypth_test_06.html, On 11th August 2012.

Library & Seminar

9.2/C3.5 Zainul, M., (1996) A Hand Book of Research for the Fellows of M. Phil and Ph. D Programmes. Dhaka: Book Syndicate. P. 23-27

Galtung, J., (1980) Theory and Methods of Social Research. New Delhi: S. chand & Co. Ltd. P. 309

Raj, H., (1981) Theory and Practice in Social Research.

 

9.2/C3.5 Zainul, M., (1996) A Hand Book of Research for the Fellows of M. Phil and Ph. D Programmes. Dhaka: Book Syndicate. P. 23-27

Galtung, J., (1980) Theory and Methods of Social Research. New Delhi: S. chand & Co. Ltd. P. 309

Raj, H., (1981) Theory and Practice in Social Research.

 

9.4/C3.5 Good, W.J. & Hatt, P.K., (1952) Methods in Social Research. 2nd ed. New York: McGraw Hill Book Company, Inc. p. 59-67

Lundberg, G.A., (1968) Social Research. 2nd ed. U.S.A.: David McKay Company, Inc. p. 117

9.5/C3.5 Good, W.J. & Hatt, P.K., (1952) Methods in Social Research. 2nd ed. New York: McGraw Hill Book Company, Inc. p. 74-76

Babbie, E., (2004) The practice of Social Research, 10th ed. Asia Thomson Learning.

9.6/C3.5 Lundberg, G. A., (1968) Social Research. 2nd ed. U.S.A.: David McKay Company, Inc. p. 120

Singh, K., (2009) Qualitative Social Research Methods. New Delhi: India Pvt. Ltd. P. 154-155

 

 

 

 

 

 

 

 

9.11 Types of Research Hypotheses

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  • Ø 9.12 How To Formulate a Hypothesis

 

 

 

 

 

 

 

 

 

 

 

 

 

  • Ø 9.12.1 Meaning of hypothesis

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  • Ø 9.12.2 Definition of hypothesis

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  • Ø 9.12.3 Characteristics of hypothesis

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  • Ø 9.12.4 Importance of hypothesis

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  • Ø 9.12.5 Difficulties of hypothesis

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  • Ø 9.12.6 Criteria of a good hypothesis

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  • Ø 9.12.7 Various types of Hypothesis

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  • Ø 9.12.8 Sources of Hypothesis

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

9.12.9 Error In Testing Hypothesis

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  • Ø 9.12.10 Conclusion

9.11/C2 Types of Research Hypotheses

Before scientists can begin working on a question that interests them, they need to formulate a research hypothesis. This is an important step in the scientific method because this determines the direction of the study. Scientists need to scrutinize previous work in the area and select an experimental design to use that helps them find data that either supports or rejects their hypothesis. Research hypotheses are of four types: null, directional, nondirectional and causal.

Null Hypothesis

This is the conventional approach to making a prediction. It involves a statement that says there is no relationship between two groups that the researcher compares on a certain variable. The hypothesis may also state that there is no significant difference when different groups are compared with respect to a particular variable. For example, “There is no difference in the academic performance of high school students who participate in extracurricular activities and those who do not participate in such activities” is a null hypothesis. In many cases, the purpose of the null hypothesis is to allow the experimental results to contradict the hypothesis and prove the point that there is a definite relationship.

Nondirectional Hypothesis

Certain hypothesis statements convey a relationship between the variables that the researcher compares, but do not specify the exact nature of this relationship. This form of hypothesis is used in studies where there is no sufficient past research on which to base a prediction. Continuing with the same example, a nondirectional hypothesis would read, “The academic performance of high school students is related to their participation in extracurricular activities.”

Directional Hypothesis

This type of hypothesis suggests the outcome the investigator expects at the end of the study. Scientific journal articles generally use this form of hypothesis. The investigator bases this hypothesis on the trends apparent from previous research on this topic. Considering the previous example, a researcher may state the hypothesis as, “High school students who participate in extracurricular activities have a lower GPA than those who do not participate in such activities.” Such hypotheses provide a definite direction to the prediction.

Causal Hypothesis

Some studies involve a measurement of the degree of influence of one variable on another. In such cases, the researcher states the hypothesis in terms of the effect of variations in a particular factor on another factor. This causal hypothesis is said to be bivariate because it specifies two aspects — the cause and the effect. For the example mentioned, the causal hypothesis will state, “High school students who participate in extracurricular activities spend less time studying which leads to a low GPA.” When verifying such hypotheses, the researcher needs to use statistical techniques to demonstrate the presence of a relationship between the cause and effect. Such hypotheses also need the researcher to rule out the possibility that the effect is a result of a cause other than what the study has examined.

(http://www.ehow.com/info_8659964_types-research-hypotheses.html, On 12th August 2012)

9.12/C2 How To Formulate a Hypothesis

Introduction:

The formulation of hypothesis or proposition as to the possible answers to the research questions is an importance steps in the process of formulation of the research problem. Hypothesis is usually considered as the principal instrument in research. Its main function is to suggest new experiment and observations. Keen observation, creative thinking, hunch, unit, imagination, vision, insight and sound judgment are of greater importance in setting up reasonable hypotheses. A thorough knowledge about the phenomenon and related fields is of great value in its process. The formulation of hypotheses plays an important part in the growth of knowledge in every science. The hypotheses are formulated to facilitate the findings of the research study.

9.12.1/C2 Meaning of hypothesis:

v The relationship between/ among variables

v The research hypothesis is a predictive statement, capable for being tested by scientific methods, that relates an independent variable to some dependent variable. The level of influence of independent variables on the dependent variables.

v E.g.: “students who receive counseling will show a greater increase in creativity than students not receiving counseling.”

v A proposal intended to explain certain facts or observations.

v A hypothesis is a precise testable statement prediction of what the researcher expects to find or prove

v It is a tentative answer to a research question.

v A hypothesis is a tentative proposition formulated for empirical testing. It is a declarative statement combining concept.

9.12.2/C2 Definition of hypothesis:

  • Ø Goode and Hatt have defined a hypothesis, “a proposition which can be put to test to determine validity.”
  • Ø According to Rummel and Balline, “A hypothesis is a statement capable of being tested and thereby verified or rejected.”
  • Ø According to M.H. Gopal ,”a hypothesis is a tentative solution posed on a cursory observation of known and available data and adopted provisionally to explain certain events and to guide in the investigation of others .It is, in fact, a possible solution to the problem.”
  • Ø A tentative theory or supposition provisionally adopted to explain certain facts, and to guide, in the investigation of others, hence, frequently called a working hypothesis.

9.12.3/C2 Characteristics of hypothesis:

Hypothesis must possess the following characteristics:

v Hypothesis should be clear and precise. If the hypothesis is not clear and precise, the inferences drawn on its basis cannot be taken as reliable.

v Hypothesis should be capable of being tested. In a swamp of untestable hypothesis, many time the research programmes have bogged down. Some prior study may be done by researcher in order to make hypothesis a testable one

v Hypothesis should state relations between variables, if it happens to be a relational hypothesis.

v Hypothesis should be limited in scope and must be specific. A researcher must remember the narrower hypothesis is generally more testable and he should develop such hypothesis.

v Hypothesis should be stated as far as possible in most simple terms so that the same is easily understandable by all concerned. But one must remember that simplicity of hypothesis has nothing to do with its significance.

v Hypothesis should be amenable to testing within a reasonable time. One should not use even an excellent hypothesis, if the same cannot be tested in reasonable time for one cannot spend a life-time collecting data to test it.

v Hypothesis must explain the facts that gave rise to the need for explanation. This means that by using the hypothesis plus other known and accepted generalization, one should be able to deduce the original problem condition. Thus hypothesis must actually explain what it claims to explain; it should have empirical reference.

9.12.4/C2 Importance of hypothesis:

Hypothesis has a very important place in research although it occupies a very small place in the body of a thesis. It is almost impossible for a research worker not to have and or more hypotheses before proceeding with his work. The importance of hypothesis can be more specifically stated as under:

It Provides direction to research. It defines what is relevant and what is irrelevant. Thus it prevents the review of irrelevant literature and the collection of useless or excess data.

It is the investigator’s eye- a sort of guiding light in the world of darkness.

• It prevents blind research. Prevents indiscriminate gathering of data which may later turn to be irrelevant.

• It places clear and specific goals before us. These clear and specific goals provide the investigator with a basis for selecting samples and research procedures to meet these goals.

• It serves the function of the linking together related facts and information and organising them in to one comprehensible whole.

• It enables the investigator to understand with greater clarity his problem and its ramifications, as well as data which beat on it.

• It serves as a formulation for drawing conclusions. It provides the outline for setting conclusions in a meaningful way.

Difficulties of hypothesis:

• There are a number of difficulties from which a beginner may suffer at the stage of formulating a good hypothesis.

• Lack of knowledge and clarity of the theoretical framework of the area in which the investigator chooses to work.

• Lack of ability to make use of the theoretical framework logically.

• Lack of acquaintance with available research technique resulting in failure to be able to phrase the hypothesis properly.

• Vagueness of the statement: For example, a course in ethics will make a student a more ethical adult.

9.12.6/C2 Criteria of a good hypothesis:

A good hypothesis must satisfy the following criteria;

  • Ø It should provide tentative answer o the proposed problem. This can be in the form of a declaration statement or in the form of a directional statement or in a null form.
  • Ø It should be operational, that is there should be a method for recording and measuring the variables involved in the hypothesis.
  • Ø It should be as simple as possible.
  • Ø It should be specific but not trivial or inconsequential. A very broad hypothesis, no doubt, makes the problem unworkable. But a very hypothesis cut the life out of it.
  • Ø A hypothesis must always be stated in advance of collecting evidence aimed at its testing. If and only if a hypothesis is stated in advance of collecting facts aimed at its testing will such facts be useful in the verification or repetition of the hypothesis.


9.12.7 Various types of Hypothesis:

1. Descriptive hypothesis:

These are propositions that describe the characteristics (such as size, form, or distribution) of a variable. The variable may be an object, person, organisation, situation or event.

Some examples are:

“The rate of unemployment among arts graduates is higher than that of commerce graduates.” “Public enterprises are more amenable for centralized planning.”

2. Relational hypothesis:

These are propositions, which describe the relationship between two variables. The relationship suggested may be positive or negative correlation or causal relationship.

Some examples:

“Families with higher incomes spend more for recreation.” “The lower the rate of job turnover in a work group, the higher the work  productivity.”

3. Casual hypothesis:

State that the existence of, or a change in, one variable causes or leads to an effect on another variables. The first variable is called the independent variable, and the latter the dependent variables the researcher must consider the direction in which such relationships flow. i.e. Which are cause and which effect is

4. Working hypothesis:

While planning the study of a problem, hypotheses are formed. Initially they are not be very specific. In such cases, they are referred to as “Working hypothesis” which are subject to modification as the investigation proceeds.

5. Null hypothesis:

These are hypothetical statements denying what are explicitly indicated in working hypothesis. They are formed in the negative statement. For example:” There is no relationship between families’ income level and expenditure on recreation”. Null hypothesis are formulated for testing statistical significance. Since, this form is a convenient approach to statistical analysis. As the test would nullify the null hypothesis, .they are so called. There is some justification for using null hypotheses. They conform to the qualities of detachment and objectivity to be possessed by a researcher. If the attempts to test hypotheses which he assumes to be true, it would appear as if he is not behaving objectively. The problem does not arise when he uses null hypotheses. Moreover, null hypotheses are more exact. It is easier to reject the contrary of hypotheses than to confirm it with complete certainty. Hence the concept of null hypothesis is found to be very useful.

6. Alternate Hypothesis {Ha}:

It is a statement, which is accepted, after a null hypotheses is rejected based on the test result. Ex: If the null hypothesis is that “there is no relationship between the eye colour of husbands and wives”, it is rejected then automatically the alternative hypothesis is that “there is relationship between the eye colour of husbands and wivesis accepted.”

7. Statistical hypothesis:

There are statements about a statistical population. These are derived from a sample. These are quantitative in nature in that they are numerically measurable, e.g., “Group A is older than Group B.”

8. Common sense Hypothesis:

These represent the common sense ideas. They state the existence of empirical uniformities perceived through day-to-day observations. “Soldiers from upper-class are less adjusted in the army than lower class men” “Fresh students conform to the conventions set up by seniors”

9. Complex Hypothesis:

 These aim at testing the existence of logically derived relationships between empirical uniformities. For example, “The concentric growth circles characterize a city”.

10. Analytical Hypothesis:

These are concerned with the relationship of analytic variables. These hypotheses occur at the highest level of abstraction. These specify relationship between changes in one property and changes in another.

9.12.8/C2 Sources of Hypothesis:

1. Theory:

This is one of the main sources of hypotheses. It gives direction to research by stating what is known logical deduction from theory leads to new hypotheses. For example, profit/wealth maximization id considered as the goal of private enterprises. From this assumption, various hypotheses are derived. “The rate of return on capital employed is an index of business success “; the optimum capital structure is that combination of debt and equity which leads to the maximum value of the firm.” “Higher the earning per share, more favorable is the financial leverage.”

2. Observation:

Hypotheses can be derived from observation. From the observation of price behavior in a market for example, the relationship between the price and demand for an article is hypothesized.

3. Analogies:

These are another resource of useful hypotheses. Julian Huxley has pointed out that casual observation in nature or in the framework of another science may be fertile source of hypotheses. For example, the hypotheses that “similar human types or activities may be found in similar geographical regions ‘came from plant ecology.

4. Intuition and personal experience:

May also contribute to the formulation of hypotheses, personal life and experiences of persons determine their perception and conception. These may, in turn, direct a person to certain hypotheses more quickly. The story of Newton and the falling apple, the flash of wisdom of Buddha under banyan tree illustrate this individual accident process.

5. Findings of studies:

Hypotheses may be developed out of the finding of other studies in order to replicate and test.

6. Culture:

Another source of hypotheses is the culture on which the researcher was nurtured.

7. Continuity of research:

The continuity of research in field itself constitutes important sources of hypotheses. The rejection of some hypotheses leads to the formulation of new once capable of explaining dependent variables in subsequent researchers on the same subject.

Procedure in testing of hypothesis:

There are five steps involved in testing of hypothesis. There are briefly discussed below.

1. Formulate a hypothesis:

The first step is to set up two hypotheses instead of one in such that if one hypothesis is true, the other is false. Alternatively, if one hypothesis is false or rejected, the other is true or accepted. That is Ho and H1.

2. Set up a suitable significance level:

Having formulated the hypothesis, the next step test its validity at a certain level of significance. The confidence with which a null hypothesis rejected or accepted depends upon the significance level used for the purpose. A significance level of, say 5%, means that in the long run, the risk of making the wrong decision is about 5%. In other words, one is likely to be wrong in accepting a false hypothesis on5 out of 100 occasions. A significance level of , say, 1% implies that there is a risk of  being wrong in accepting or rejecting the hypothesis on 1 out of 1oo occasions. Thus, a 1% significance level provides greater confidence to the decision than a 5%significance level.

3. Select test criterion:

The next step in hypothesis is testing is the selection of an appropriate statistical technique as a test criterion. There are many techniques from which one is to be chosen. For example, when the hypothesis pertains to a large sample of more than 30, the z test implying normal distribution is used. When a sample is small (less than 30), the t-test will be more suitable. The test criteria that are frequently used in hypotheses testing are z, t, f & χ2

4. Compute:

After having selected the statistical technique to test the hypotheses, the next step involves various computations for the application of that particular test. These computations include the testing statistics as its standard error.

5. Make decisions:

The final step in hypothesis testing is to draw a statistical decision, involving the acceptance or rejection of the null hypothesis. This will depend on whether the computed value of the test criterion falls in the region of acceptance or in the region of rejection at a given level of significance. It may be noted that the statement rejecting the hypothesis is much stronger than the statement accepting it. It is much easier to prove something false than to prove it true. Thus when we say that the null hypothesis is not rejected, we do not categorically say that it is true.

9.12.9/C2 ERROR IN TESTING

Type I Error (α):

It refers to the rejection of a null hypothesis when it is true. The Ierror is symbolized by α (alpha)

Type II Error (β):

Accepting a null hypothesis when it is false is called type II error which is symbolized by β (beta) In the test of a null hypothesis the possible decisions.

is true Correct decision Incorrect decision (Type I error) H0

is false Incorrect decision (Type II error) Correct decision

In the form of probability:

α =P (Type I error) = P (Reject H0/ H0 true)

β =P (Type II error) = P (Accept H0/ H0 false)

9.12.10/C2 Conclusion:

It is true that hypotheses are useful and they guide the research process in the proper direction. In fact, many experiments are carried out with the deliberate object of testing hypothesis. Decision-Makers often face situations wherein they are interested in testing hypothesis on the basis of available information and then take decisions on the basis of such testing. But in all analytical and experiment studies, hypothesis should be setup in order to give a proper direction to them.

The hypothesis will guide a researcher in the selection of pertinent facts that are required to explain the issue considered for the study. Thus, formulation of hypothesis plays an important role in the research studies.

(http://www.scribd.com/doc/29008297/hypothesis#download, On 6th August, 2012.)

 
  • Ø 9.13 ভূমিকা

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  • 9.13.1 পূর্বানুমানের কার্যাবলী

9.13.2 বৈধ পূর্বানুমানেরশর্তসমূহ

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  • Ø 9.13.3 পূর্বানুমানের প্রকারভেদ
  • Ø 9.13.4 পূর্বানুমানের গঠন
  • 9.13.5 পূর্বানুমান,তত্ত্ব, আইন এবং ঘটনার মধ্যে সম্পর্ক

9.13/C2 ভূমিকাঃ

পূর্বানুমান হচ্ছে পরীক্ষামূলক সর্বজন স্বীকৃত একটি অনুমান/ধারণা যেটি বৈধতা পরীক্ষণের জন্য গ্রহণ করা হয়। প্রাথমিক পর্যায়ে পূর্বানুমান কোন ধারণা বা অনুমান হিসেবে মনে করা হয় এবং পূর্বানুমানের উপর ভিত্তি করে এটি গ্রহণ করা হয়। অনুসন্ধানের মাধ্যমে ঐ ধারণাটির সঠিক ব্যাখ্যা জানার জন্য পূর্বানুমান করা হয়। পূর্বানুমানের উপর ভিত্তি করে বিভিন্ন বিষয়ে পর্যবেক্ষণ করা হয় এবং তথ্য সংগ্রহ করা হয়। সে সব তথ্যের সাহায্যে ধারণাটির সত্যতা যাচাই করা হয়। এরপর ধারণাটি গ্রহণ বা বর্জন করা হয়। যখন অনুসন্ধান এবং প্রাপ্ত তথ্যের ভিত্তিতে পূর্বানুমানটি সত্য বলে প্রমাণিত হয় তখন তা একটি মতাদর্শ বা থিউরি হিসেবে গ্রহণ করা হয়।

যেমনঃ সরকার থেকে বৃত্তি পাওয়ার কারণে মেয়েদের শিক্ষার হার বৃদ্ধি পাচ্ছে। এটি একটি পূর্বানুমান। এর উপর ভিত্তি করে বিভিন্ন অনুসন্ধান এবং তথ্যের মাধ্যমে এর সত্যতা যাচাই করা হবে এবং যখন এটি সত্য বলে প্রমাণিত হবে তখন এটি একটি মতবাদ বা থিউরিতে রূপ লাভ করবে।

9.13.1/C2 পূর্বানুমানের কার্যাবলীঃ

সামাজিক গবেষণায় পূর্বানুমানের কার্যাবলী অনস্বীকার্য। সদা পরিবর্তনশীল সমাজে বিভিন্ন বিষয় নিয়ে অনুসন্ধান পরিচালনার ক্ষেত্রে পূর্বানুমান অন্যতম চালিকাশক্তি হিসেবে কাজ করে। নিচে পূর্বানুমানের কার্যাবলী বর্ণনা করা হলো-

১। তথ্যের সঠিক ব্যাখ্যা প্রদানঃ

পূর্বানুমানের সবচেয়ে গুরুত্বপূর্ণ কাজ হচ্ছে পূর্বানুমানের সাথে সংশ্লিষ্ট তথ্যগুলো সঠিক এবং স্পষ্টভাবে ব্যাখ্যা করা।

২। তথ্য সংগ্রহঃ

পূর্বানুমান সঠিক পথে তথ্য সংগ্রহ করতে সহায়তা করে থাকে। এক্ষেত্রে পরীক্ষণ বা পর্যবেক্ষণ পদ্ধতির মাধ্যমে প্রয়োজনীয় তথ্য সংগ্রহ করা যেতে পারে।

৩। গবেষণা পদ্ধতি ও পরিসর নির্ধারণঃ

পূর্বানুমানের মাধ্যমে গবেষণা পদ্ধতি নির্ধারণ করা হয়। এর মাধ্যমে গবেষণার উপযুক্ত পরিসর নির্ধারণ করা হয়, ফলে পূর্বানুমানের সাথে প্রাসঙ্গিক তথ্যগুলোই সংগ্রহ করা হয়।

৪। সময় ও অর্থ সাশ্রয়ীঃ

পূর্বানুমানের মাধ্যমে গবেষণার নির্দিষ্ট পরিসর নির্ধারণ করা হয় ফলে গবেষণাকার্যে সময় এবং অর্থ সাশ্রয় হয়।

৫। বিধি প্রতিষ্ঠাঃ

তথ্য সংগ্রহের পর যখন তা পূর্বানুমানের সাথে মিলে যায় এবং তা অন্যান্য বিষয় গুলোকে যখন প্রতিনিধিত্ব করে,তখন তা বিধি বা আইনে পরিণত হয়।


৬। নতুন জ্ঞানের প্রসার সাধনঃ

পূর্বানুমান হতে প্রাপ্ত তথ্যের ভিত্তিতে যে উপসংহার টানা হয় তা পুরাতন জ্ঞানের ভিত্তিতে নতুন জ্ঞানের আবিষ্কারে সহায়তা প্রদান করে। তাছাড়া পূর্ববর্তী গবেষণার যে অপূর্ণতা থাকে তা পূরণের ক্ষেত্রেও পূর্বানুমান গুরুত্বপূর্ণ ভূমিকা পালন করে।

9.13.2/C2 বৈধ পূর্বানুমানেরশর্তসমূহঃ

যে কোন ধারণা বা অনুমান গবেষণা কাজে ব্যবহারের উপযোগী নয়। একটি সাধারণ ধারণা বা পূর্বানুমানকে উত্তম ব্যবহার উপযোগী হিসেবে বিবেচিত হতে হলে বিশেষ কিছু শর্ত মানতে হয়। নিচে সেগুলো আলোচনা করা হল-

১। প্রায়োগিকঃ

একটি বৈধ বা উত্তম পূর্বানুমান বা ধারণার সবচেয়ে গুরুত্বপূর্ণ শর্ত হচ্ছে প্রায়োগিক সত্যতা। অর্থাৎ প্রাপ্ত তথ্যের ভিত্তিতে পূর্বানুমানের সত্যতা যদি যাচাই করা না যায় তবে সে ধারণাটি বৈধতা অর্জন করতে পারবে না। অন্যথায় এটি কেবল মাত্র ধারণাই থেকে যাবে।

২। সমস্যার উত্তর প্রদানঃ

একটি উত্তম/বৈধ পূর্বানুমান অবশ্যই সমস্যা সমাধানের উপায় বলে দেবে। অর্থাৎ যখন কোন পূর্বানুমান সমস্যার উত্তর দিতে পারে তখন পূর্বানুমানটি বৈধ হবে।

যেমনঃ মেয়েদের শিক্ষার হার কম কেন তা অনুসন্ধান করা। যখন পূর্বানুমান এই সমস্যার প্রায়োগিক উত্তর দিতে পারবে তখন তা বৈধ হবে।

তবে একটি মিথ্যা পূর্বানুমান বা ধারণা ব্যবহার অনুপযোগী নয়। কারণ এর মাধ্যমে পুনরায় গবেষণায় উৎসাহ জাগতে পারে যা নতুন কিছু আবিষ্কারে সাহায্য করে।

৩। তত্ত্বের সাথে সম্পর্কযুক্তঃ

একটি ধারণা বা পূর্বানুমান তখনই বৈধ হবে যখন ধারণাটি প্রতিষ্ঠিত জ্ঞান বা তত্ত্বের পক্ষে যায়। যেমন- “একাকীত্ববোধ অপরাধ প্রবণতার জন্ম দেয়।“ একটি ধারণা যদি সুপ্রতিষ্ঠিত ধারণার বিরুদ্ধে যায় তাহলে সেটি অবৈধ নাও হতে পারে। কিন্তু কোন তত্ত্বের বিপরীতে গেলে সেটি বৈধ নাও হতে পারে।

৪। সহজ, সরল ও সুনির্দিষ্ট ধারণাঃ

একটি পূর্বানুমানকে অবশ্যই সুনির্দিষ্ট হতে হবে। তাছাড়া পূর্বানুমান গবেষক ব্যক্তিগত কারণে করে না বরং তা অন্যের স্বার্থে করে। সুতরাং এটি অবশ্যই সহজ,সরল হতে হবে।     

৫। বর্তমান জ্ঞানকে প্রতিনিধিত্ব করাঃ

পূর্বানুমান তখনই বৈধ হবে যখন তা বর্তমান প্রতিষ্ঠিত জ্ঞানের ক্ষেত্রে সত্য বলে প্রমাণিত হয়। একটি কাল্পনিক ধারণা বা অযৌক্তিক কল্পনা কখনও বৈধ পূর্বানুমান হতে পারে না।

পরিশেষে বলা যায় যে,পূর্বানুমানের ক্ষেত্রে উপরোক্ত বৈধতা সম্পর্কে গবেষককে অত্যন্ত সচেতনভাবে অগ্রসর হতে হয়। কারণ গবেষণার ব্যর্থতার জন্য পূর্বানুমানের বৈধতা একটি অন্যতম প্রভাবক।

9.13.3/C2 পূর্বানুমানের প্রকারভেদঃ

পূর্বানুমানকে প্রধানত দুটি ভাগে ভাগ করা যায়। যথাঃ

১। Crude (অশোধিত)

২। Refined (শোধিত)

নিচে এগুলো আলোচনা করা হল-

১। Crude (অশোধিত):

এ ধরণের পূর্বানুমান বা ধারণা সাধারণত নিম্ন পর্যায়ের হয়ে থাকে, যেখানে বাস্তব জগতের সাথে সামঞ্জস্যপূর্ণ বিষয় সম্পর্কে ধারণা করা হয়। এ ধরণের পূর্বানুমান দ্বারা উন্নত তাত্ত্বিক গবেষণা করা সম্ভব হয় না।

যেমনঃ বাংলাদেশের শহরগুলোতে ছেলেদের মধ্যে বিবাহের প্রবণতা সম্পর্কে একটি প্রকল্প/ পূর্বানুমান হতে পারে, “বাংলাদেশের শহুরে ছেলেদের মধ্যে বেশির ভাগই ২০-২৫ বছর বয়সে বিবাহ বন্ধনে আবদ্ধ হয়।”

২। Refined (শোধিত):

গবেষণার ক্ষেত্রে এ ধরণের পূর্বানুমান খুবই তাৎপর্যপূর্ণ। অপেক্ষাকৃত উচ্চতর পর্যায়ের প্রকল্পে বিভিন্ন ধরণের সাধারণ ধারণা বা প্রাকৃতিক জগতের সামঞ্জস্যপূর্ণতার মধ্যে যৌক্তিক সম্পর্ক নির্ণয়ের চেষ্টা করা হয় এবং এসব সম্পর্কের সত্যতা যাচাই করা হয়।

রিফাইন্ড পূর্বানুমানকে আবার তিন ভাগে বিভক্ত করা যায়-

ক) The simple level

খ) Complex level

গ) The very complex

নিচে এগুলো সম্পর্কে বিস্তারিত আলোচনা করা হল-

ক) The simple level:

এ ধরণের পূর্বানুমান প্রচলিত সামাজিক আচার-আচরণকে বুঝায়। এর মাধ্যমে তেমন কোন সত্যতা যাচাই করা হয় না।

খ) Complex level:

এই ধরণের পূর্বানুমান উচ্চ পর্যায়ের বস্তুনিষ্ট বিষয়ের ক্ষেত্রে করা হয়ে থাকে। এর মাধ্যমে প্রায়োগিক সাদৃশ্যগুলোর মধ্যে যৌক্তিক সম্পর্ক পরীক্ষা করা হয়। এই ধরণের পূর্বানুমান গবেষণা উপকরণের উন্নয়নে কার্যকরী ভূমিকা পালন করে। এটি পরবর্তী পূর্বানুমান বা ধারণা গঠনে সহায়তা করে।

গ) The very complex:

এই ধরণের পূর্বানুমান বা ধারণা খুবই জটিল প্রকৃতির। এর মাধ্যমে একাধিক চলকের মধ্যে আন্তঃসম্পর্ক নির্দেশ করে।

যেমনঃ অনুন্নত দেশগুলোতে পরিবার পরিকল্পনা এবং জনসংখ্যা বৃদ্ধি নিয়ে যদি গবেষণা করা হয় তবে, বেশ কিছু, জটিল বিষয় যেমন-সম্পদ,ধর্ম, সংস্কৃতি,ঐতিহ্য,স্বাস্থ্য ইত্যাদি বিষয়গুলো অবশ্যই বিবেচনা করতে হবে।

9.13.4/C2 পূর্বানুমানের গঠনঃ

পূর্বানুমানের গঠন গুলো নিচে আলোচনা করা হল-

1. Hypothesis concerning law:

এর মাধ্যমে ব্যাখ্যা করা হয় কেমন করে একজন প্রতিনিধি কোন নির্দিষ্ট ঘটনাকে প্রভাবিত করে। এক্ষেত্রে যে কাজটি করা হবে তার আইনগত বৈধতা থাকবে যা সকলে আইন হিসেবে জানবে।

2. Hypothesis concerning an agent:

যে কাজটি করা হবে সে আইন সম্পর্কে সকলে জানবে। কিন্তু যে কুশলীর দ্বারা এ আইনের সৃষ্টি সে সম্পর্কে কেউ জানবে না। এই ধরণের পূর্বানুমান গঠন করা হয় এই কুশলী খুঁজে বের করার জন্য।

3. Hypothesis concerning collection:

পাশাপাশি অবস্থান বলতে বোঝায় বিভিন্ন ঘটনা একত্রীকরণ।এই পদ্ধতিতে পূর্বানুমান বা ধারণার দ্বারা ইন্দ্রিয়গ্রাহ্য ঘটনা উদঘাটনের জন্য প্রয়োজনীয় ঘটনার সাথে সংযোগ স্থাপন করা হয়।

4. Descriptive hypothesis:

এ পদ্ধতিতে কোন ঘটনার সাথে সম্পৃক্ত কারণ ও ফলাফলের মধ্যে সম্পর্ক বর্ণনা করা হয়।

5. Explanatory hypothesis:

কোন একটা ঘটনা কেন ঘটেছে তা অনুসন্ধান করার জন্য এই পদ্ধতি ব্যবহার করা হয়। এই পদ্ধতিতে পূর্বে প্রতিষ্ঠিত কোন তথ্যাদি বিচারের মাধ্যমে অজ্ঞাত কোন কিছুর মূল্য বিচার ও বিভিন্ন ঘটনা একত্রিত করে কোন একটি ঘটনার পুনঃগঠন করে।

9.13.5/C2 পূর্বানুমান,তত্ত্ব,আইন এবং ঘটনার মধ্যে সম্পর্ক (Hypothesis, Theory, Law and Fact Relation):

পূর্বানুমান, তত্ত্ব, আইন এবং ঘটনা এগুলো একে অন্যের সাথে খুবই সম্পৃক্ত। অনুসন্ধানের প্রথম পর্যায়ে একটি পূর্বানুমান নির্ধারণ করা হয়, যেটি শুধুমাত্র একটি পরীক্ষামূলক ধারণা বা অনুমান। যখন কোন পূর্বানুমানের সত্যতা যাচাই করা হয় এবং এক পর্যায়ে সত্য বলে প্রমাণিত হয়,তখন এটি তত্ত্বে পরিণত হয়। যখন এই তত্ত্ব প্রমাণিত হয় এবং জনসাধারণ আগ্রহের সাথে গ্রহণ করে, তখন এটি পুনরায় ব্যাখ্যা ও অনুমান করা হয়। এই পর্যায়ে এটি আইনে পরিণত হয়।

ঘটনা হচ্ছে একটি বাস্তব জ্ঞান। এটি হতে পারে অভ্যন্তরীণ বা বাহ্যিক (মনের) বিষয়। যেমন- নারী ও পুরুষের সমান অধিকার প্রতিষ্ঠা করা। বাস্তবতার দিক থেকে কোন ঘটনাই পূর্বানুমানে উৎসাহিত করে। এই পূর্বানুমান তত্ত্বে পরিণত হয়; তত্ত্ব আইনে, এবং আইন যখন জনপ্রিয় হয় তখন এটি পুনঃরায় ঘটনায় রূপান্তরীত হয়।

(Kothari, C. R., (1999) Research Methodology Methods & Technique. India: Wishwa Prakashan. {বাংলায় অনুবাদিত})

 

 

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