Updated: Jan 30
For the first few years teaching AP Statistics, our goal for the end of the course was simple:
“If the P-value is low, the null must go!”
With this as the goal, students cruise through their calculations (or punch buttons on the calculator) without thinking too much about the mechanics. All they need to know is the number for that P-value and they are ready to write a scripted conclusion.
This approach seemed to work reasonably well, but students were still struggling with many concepts related to significance tests, including:
Lack of intuition about whether or not sample data will be statistically significant
Forgetting that a significance test is performed by assuming the null hypothesis is true
Difficulty in connecting their decision (reject the null or fail to reject the null) to a conclusion in the context of the problem
Struggling to understand how to improve the power of a significance test or to shift probabilities for Type I and Type II errors.
After a few years of using this memorize-a-catch-phrase approach, we realized that students didn’t really understand the P-value (like most of the population of adults!). We decided to set an intentional goal for students to be able to interpret the P-value (the holy grail of AP Statistics).
Here are 3 specific strategies to make this happen:
1. Use simulation to develop the concept informally
Don’t wait until the significance test chapter in the book to start developing the conceptual understanding of a P-value. There are plenty of opportunities in our curriculum to sneak the P-value into an activity. Here are a few:
“Assuming that Joy can’t smell Parkinsons’ disease, there is a 0/25 = 0 probability she would correctly guess 11 or more correct out of 12, purely by chance.”