Hypothesis Tests of a Population Mean

This chapter focuses on using sample data to test hypotheses regarding the population mean. A sample of data was taken, the sample mean was calculated, and then compared to the hypothesized mean. If the sample mean was far enough away from the hypothesized mean, then the null hypothesis is rejected. The test statistic results in how many standard errors the sample mean is from the hypothesized mean. The test statistic is compared with a critical value, or by comparing the p-value to the level of significance. There are two types of errors that can be made with hypothesis testing. A Type I error is when a null hypothesis is rejected when in reality it is correct. The second type of error is called a Type II error, and is made when we fail to reject a null hypothesis that is actually false. The most common type of hypothesis tests is two-tailed.