if the value of the test statistic falls outside the critical region, then there is not enough evidence to reject the null hypothesis at the chosen significance level.if the value of the test statistic falls inside the critical region, then the null hypothesis is rejected at the chosen significance level.This region is chosen such that the probability of the test statistic falling in the critical region when the null hypothesis is correct (Type I error) is equal to the previously chosen level of significance (α). Based on the hypotheses, test statistic, and sampling distribution of the test statistic, we can find the critical region of the test statistic which is the set of values for the statistical test that show evidence in favor of the alternative hypothesis and against the null hypothesis. Hypotheses: Null (H 0) and Alternative (H 1)īefore observing the data, the null and alternative hypotheses should be stated, a significance level (α) should be chosen (often equal to 0.05), and the test statistic that will summarize the information in the sample should be chosen as well.Inferential Statistics - Hypothesis Testing Perform and interpret a paired t-test using proc ttest.Perform and interpret a one sample t-test using proc ttest.Explain and use the standard normal distribution.Explain what is meant by Type I and Type II errors.Outline the components of a statistical test.After successfully completing this module, the student will be able to:
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