This chapter introduces the t test, a statistical tool for hypothesis testing in which the population variance is unknown. After reading this chapter, you should:
- understand when to use a t test for a single sample and how it differs from methods discussed in previous chapters;
- understand how the variance of a sample differs from the variance of a population and know how to compute an unbiased estimate of the population variance and the standard deviation of the distribution of means;
- understand what a t distribution is and how it differs from a normal distribution;
- know how to compute a t score and compare it to the cutoff scores on a t table;
- understand when to use a t test for dependent means and how it differs from a t test for a single sample;
- understand the assumptions of the t test;
- understand how to determine effect size and power for the t test.
