Discuss how the t-test for correlated groups and the t-test for single samples are alike and different. Give a current example to support your answer. t-test for correlated groups and the t-test for single samples

Performs a one-sample t-test in order to compare an individual population to a standard value (for example, to determine whether life expectancy in a given city differs from the national average). Paired t-tests are used to compare data from a single population before and after an experimental intervention or at two different time points (for example, comparing student test scores before and after teaching material) (Gerald, 2018). A correlated t-test analyzes the means of two related groups to determine whether there is a statistically significant difference between these means (also known as a paired t-test or a paired-sample t-test) (Zhang et al., 2021). As we saw above, the one-sample t-test compares the mean of the sample to the value of the null hypothesis. A paired t-test simply calculates the difference between paired observations (such as before and after) and then performs a 1-sample t-test on the results. The former is used when the independent variable is between subjects in nature, while the latter is used when the independent variable is within individuals. This is the main difference between related groups t-test and independent groups t-test. continue…