MBA Hypothesis Testing in Research Methodology

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Notes on Hypothesis Testing in Research Methodology:

Procedure Of Hypothesis Testing:
Testing a hypothesis refers to verifying whether the hypothesis is valid or not. Hypothesis testing attempts to check whether to accept or not to accept the null hypothesis. The procedure of hypothesis testing includes all the steps that a researcher undertakes for making a choice between the two alternative actions of rejecting or accepting a null hypothesis. The various steps involved in hypothesis testing are as follows:

1) Making a Formal Statement:
This step involves making a formal statement of the null hypothesis (H0) and the alternative hypothesis (Ha). This implies that the hypotheses should be clearly stated within the purview of the research problem. For example, suppose a school teacher wants to test the understanding capacity of the students which must be rated more than 90 per cent in terms of marks, the hypotheses may be stated as follows:

2) Selecting A Significance Level:
The hypotheses should be tested on a pre-determined level of significance, which should be specified. Usually, either 5% level or 1% level is considered for the purpose. The factors that determine the levels of significance are: (a) the magnitude of difference between the sample means; (b) the sample size: (c) the variability of measurements within samples; and (d) whether the hypothesis is directional or non-directional (Kothari, 1988). In sum, the level of significance should be sufficient in the context of the nature and purpose of enquiry.

3) Deciding The Distribution To Use:
After making decision on the level of significance for hypothesis testing, the researcher has to next determine the appropriate sampling distribution. The choice to be made generally relates to normal distribution and the t-distribution. The rules governing the selection of the correct distribution are similar to the ones already discussed with respect to estimation.

4) Selection Of A Random Sample And Computing An Appropriate Value:
Another step involved in hypothesis testing is the selection of a random sample and then computing a suitable value from the sample data relating to test statistic by using the appropriate distribution. In other words, it involves drawing a sample for furnishing empirical data.

5) Calculation Of The Probability:
The next step for the researcher is to calculate the probability that the sample result would diverge as far as it can from expectations, under the situation when the null hypothesis is actually true.

6) Comparing The Probability:
Another step involved consists of making a comparison of the probability calculated with the specified value of α, i.e. The significance level. If the calculated probability works out to be equal to or smaller than the α value in case of one-tailed test, then the null hypothesis is to be rejected. On the other hand, if the calculated probability is greater, then the null hypothesis is to be accepted. In case the null hypothesis H0 is rejected, the researcher runs the risk of committing the Type I error. But, if the null hypothesis H0 is accepted, then it involves some risk (which cannot be specified in size as long as H0 is vague and not specific) of committing the Type II error.

Research design in the case of hypothesis testing research studies:
Hypothesis testing research studies are generally known as experimental studies. This is a study where a researcher tests the hypothesis of causal relationships between variables. This type of study requires some procedures which will not only reduce bias and increase reliability, but will also permit drawing inferences about causality.
Most of the times, experiments meet these requirements. Prof. Fisher is considered as the pioneer of this type of studies (experimental studies). He did pioneering work when he was working at Rothamsted Experimental Station in England which was a centre for Agricultural Research. While working there, Prof. Fisher found that by dividing plots into different blocks and then by conducting experiments in each of these blocks whatever information that were collected and inferences drawn from them happened to be more reliable. This was where he was inspired to develop certain experimental designs for testing hypotheses concerning scientific investigations. Nowadays, the experimental design is used in researches relating to almost every discipline of knowledge. Prof. Fisher laid three principles of experimental designs:

1. The Principle of Replication
2. The Principle of Randomization and
3. The Principle of Local Cont