Promotions Activity

Introduction and needed packages

Now that we’ve studied confidence intervals, let’s study another commonly used method for statistical inference: hypothesis testing. Hypothesis tests allow us to take a sample of data from a population and infer about the plausibility of competing hypotheses. For example, in the upcoming promotions activity, we’ll study the data collected from a psychology study in the 1970s. We’ll study this data to investigate whether gender-based discrimination in promotion rates existed in the banking industry at the time of the study.

There was one general framework that applies to all confidence intervals and the infer package was designed around this framework. While the specifics may change slightly for different types of confidence intervals, the general framework stays the same.

We believe that this approach is much better for long-term learning than focusing on specific details for specific confidence intervals using theory-based approaches. As we’ll now see, we prefer this general framework for hypothesis tests as well.