ABSTRACT
This chapter discusses types of hypotheses, types of decision errors and level of significance. Hypothesis testing is a decision-making process where two possible decisions are weighed in a statistical fashion. The null or statistical hypothesis is a statement about the value of an unknown population parameter. The null hypothesis is basically set up by the researcher in an attempt to reject the null hypothesis in favor of our own personal scientific, alternative, or research hypothesis. The chapter considers more specifically the types of decision errors that might be made in the decision-making process. Two other alternative hypotheses are also possible, depending on the researcher’s scientific hypothesis, which are known as directional alternative hypotheses. The chapter also discusses the basic steps for hypothesis testing of any inferential test, which is state, the null and alternative hypotheses, select the level of significance, calculate the test statistic value, and make a statistical decision.
