Question

discuss the differences between a one-sample z-test, one-sample t-test, the independent samples t-test and the dependent samples t-test. Specifically, under what circumstances would you conduct each test and what type of information comes from a known/defined population versus your sample data?

Answer 1

Following are the differences and cases to use the following tests

• One Sample Z-test: It is used when we know the population variance and can be used for one population (or two population).
• One Sample t-test: It is used when we want to find whether the mean is different from a hypothesized value or the mean of the population and we don't know the population variance.
• Independent Samples t-test: Used when we compare the mean difference between two data sets. In this case, the subjects are different in both cases. Samples are independent
• Dependent Samples t-test: Used when we compare the mean difference between two data sets. The same subject is measured twice, once in one condition and 2nd in different conditions. Samples are related