Statistical Hypothesis Testing

A statistical hypothesis is a hypothesis that is testable, on the basis of observing a process modeled by a set of random variables that follow a probability distribution known a priori. Hypothesis testing (or confirmatory data analysis) is a method of statistical inference that resorts to tests of significance to determine the probability that a statement is true, and at what likelihood such a statement may be accepted as true. This chapter explains basic process of hypothesis testing that consists of four sequential steps: formulation of the null hypothesis, H 0; identification of an appropriate test statistic that can be used to assess the truth of the null hypothesis (dependent on the nature of the data and of the test); computation of the P-value, or associated probability that a test statistic at least as significant as the one determined from the sample data would be obtained; and comparison of the P-value with an acceptable significance level.