What you’ll learn to do: Construct and interpret an appropriate hypothesis test to compare two population/treatment group proportions.
In this section we will learn to conduct a hypothesis test for comparing two population proportions or two treatments, under the appropriate conditions, and state a conclusion in context. We can use this to analyze real world examples such as insurance coverage as well as teen depression rates. We will also interpret the P-value as a conditional probability. Then we will then identify type I and type II errors and select an appropriate significance level based on an analysis of the consequences of each type of error.
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