# Chapter Summary

### Chapter 9

Statistical hypothesis testing is a deci­sion-making process that enables us to deter­mine whether a particular sample result falls within a range that can occur by an accept­able level of chance.The process of statistical hypothesis testing consists of five steps: (1) making assumptions, (2) stating the research and null hypotheses and selecting alpha, (3) selecting a sampling distribution and a test sta­tistic, (4) computing the test statistic, and (5) making a decision and interpreting the results.

Statistical hypothesis testing may involve a comparison between a sample mean and a population mean or a comparison between two sample means.If we know the population variance(s) when testing for dif­ferences between means, we can use the Z sta­tistic and the normal distribution.However, in practice, we are unlikely to have this information.

When testing for differences between means when the population variance(s) are unknown, we use the t statistic and the t distribution.

Tests involving differences between pro­portions follow the same procedure as tests for differences between means when population variances are known.The test statistic is Z, and the sampling distribution is approximated by the normal distribution.