**PROCEDURE FOR TESTING OF HYPOTHESIS**

**a)State the Null Hypothesis as well as the alternative hypothesis**

In the context of statistical analysis, we often talk about null hypothesis and alternative hypothesis. The null hypothesis is generally symbolized as** Ho.** Null hypothesis states that there is no difference between the parameter and the statistic that is being compared. In this case the statistician adopts the neutral attitude towards testing process

Any hypothesis which is complementary to null hypothesis is known as alternative hypothesis and it is denoted by H_{1}**.** In other words the hypothesis which contradicts the null hypothesis according to the question is known as alternative hypothesis

**Example: **

- If we want to test the hypothesis that whether the population mean µ is 100 or not then: H
_{o}: µ=100 and H_{1}: µ ≠ 100 (two tailed test) - If we want to test the hypothesis that whether the population mean µ is more than100 or not then: H
_{o}: µ=100 and H_{1}: µ > 100 (right tailed test) - If we want to test the hypothesis that whether the population mean µ is less than100 or not then: H
_{o}: µ=100 and H_{1}: µ < 100 (left tailed test)

** b) Establish a level of Significance**

Having setup the hypothesis, the next step is to test the validity of Ho against H_{1} at a certain level of significance. The probability level with which an experimenter rejects or accepts **H _{0} **is known as the level of significance. Two most commonly used levels of significance are 0.5 (5%) level and 0.01 (1%) levels. These levels correspond to the confidence coefficients of 0.95 (95%) and 0.99 (99%) respectively.

**c)** **Selecting a random sample and computing an appropriate value**

Another step is to select a random sample and compute an appropriate value from the sample data concerning the test statistic utilizing the relevant distribution. In other words, draw a sample to furnish empirical data.

**d)** **Choosing a suitable test statistic**

Now the researcher would choose amongst the various tests. A suitable statistic called ‘test statistics’ is chosen for the purpose of rejecting or accepting the null hypothesis.

**e) Drawing Conclusion:**

If the calculated value obtained in the last step using appropriate test statistic is less than the critical value (tabulated value) then the null hypothesis is accepted and the alternative hypothesis is rejected at the pre-determined level of significance for manual testing of hypothesis.

Similarly, if the p-value is less than 0.05 then the null hypothesis is rejected and alternative hypothesis is accepted at 5% level of significance for hypothesis testing using SPSS.