2. Identify a test statistic that can be used to assess the truth of the null hypothesis. 3. Compute the P-value, which is the probability that a test statistic at least as significant as the one observed would be obtained assuming that the null hypothesis were true. The smaller the -value, the stronger the evidence against the null hypothesis. 4. Compare the -value to an acceptable significance value (sometimes called an alpha value). If , that the observed effect is statistically significant, the null hypothesis is ruled out, and the 21
alternative hypothesis is valid. Flow Diagram 1 Identify the null hypothesis H0 and the alternate hypothesis HA. 2 Choose ,The value should be small, usually less than 10%. It is important to consider the consequences of both types of errors. 3 Select the test statistic and determine its value from the sample data. This value is called the observed value of the test statistic. Remember that a t statistic is usually appropriate for a small number of samples; for larger number of samples, a z statistic can work well if data are normally distributed. 4 Compare the observed value of the statistic to the critical value obtained for the chosen ?. 5 Make a decision. If the test statistic falls in the critical region: Reject H0 in favor of HA. If the test statistic does not fall in the critical region: Conclude that there is not enough evidence to reject H0 The research design should be based 1.What is the study about? 2.Why is the study being made? 3.Where will the study be carried out? 4.What type of data is required? 5.Where can the required data be found? 6.What will be the sample design? 7.What techniques of data collection will be used? 8.How will the data be analyzed? 9.In what style will the report be prepared?
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