Section 9.1 Summary

1. Statistical hypothesis testing is a way of formalizing the decision-making process so that a decision can be rendered about the unknown value of the parameter. The status quo hypothesis that represents what has been tentatively assumed about the value of the parameter is called the null hypothesis and is denoted as . The alternative hypothesis, or research hypothesis, denoted as , represents an alternative statement about the value of the parameter.
2. When performing a hypothesis test, there are two ways of making a correct decision: to not reject when is true and to reject when is false. Also, there are two types of errors: a Type I error is to reject when is true, and a Type II error is to not reject when is false. The probability of a Type I error is denoted as (alpha). The probability of a Type II error is denoted as (beta).