ABSTRACT
This chapter shows how to deal with hypothesis testing. A hypothesis is a statement about the parameters of the model. Hypotheses can be of two types. If the hypothesis fully specifies all the parameters of the model it is called simple. Otherwise it is called composite. The chapter discusses error probabilities for a one-sided test of the mean in a normally distributed population. It describes the test of a proportion based on a large sample and the test of a mean based on a large sample. The chapter illustrates the test of the difference between two means based on a large sample as well as the test of the difference between two proportions in a large sample. It also includes exercise problems related to hypothesis testing.
