Why is t needed?
The process for calculating p-values is to start with the sample statistic, standardize it to get a test statistic, then transform it via a cumulative distribution function. In Chapter 1, that final transformation was denoted z
, and the CDF transformation used the (standard normal) z-distribution. In the last video, the test statistic was denoted t
, and the transformation used the t-distribution.
In which hypothesis testing scenario is a t-distribution needed instead of the z-distribution?
This exercise is part of the course
Hypothesis Testing in R
Hands-on interactive exercise
Turn theory into action with one of our interactive exercises
