know the definition of the Type 1 and Type II error; explain why the Type I error is the most serious error; understand how to set-up the appropriate alternatives given a description of the required Type I error for the a given problem; know how to conducted a hypothesis test and to report the conclusions (for large and small samples); know how to calculate the p-value; understand the significance of the p-value as an alternative to traditional method of hypothesis testing; know how to calculate the beta-risk; understand why it is important to calculate the beta-risk; understand how to interprete the beta-risk for different values of the population mean.

know how to conduct a hypothesis test for large sample; know how to test if sample size is large.  (All the general points discussed for population mean also  apply to population proportions.)

understand the type of problems for which hypothesis testing fo variance is important; know the variable that is used for hypothesis testing of variance; know the sampling distribution of this variable; know how to get the rejection region from the chi-square table.