New School Year, New Applets!

Today's blog post comes from AP Stats gurus Josh Tabor and Bob Amar.

Josh Tabor is an AP Statistics teacher at The Potter's School. He is a long-time AP Reader, Table Leader, and Question Leader and presents workshops around the country. He is also the co-author of The Practice of Statistics for AP Statistics and two textbooks for on-level statistics: Statistics and Probability with Applications and Statistical Reasoning in Sports.

Bob Amar is the Upper School Math Department Head at The Lovett School in Atlanta, GA. A math teacher since 2006, he has taught all levels of high school math, including AP Calculus and AP Statistics, and has been a reader for AP Statistics the past three years. Bob is the programmer of the web-based support software for Statistical Reasoning in Sports and Statistics and Probability with Applications, from which Stapplet was born and continues to evolve.

We are excited to announce the arrival of several new applets at (also available at If you haven't been to before, it is a collection of statistical applets (st-applets) that was originally designed to be a graphing calculator replacement for students who already have internet connected devices, such as laptops, iPads, or smart phones. Over the years, the collection has expanded to include activities and the ability to collaboratively collect data. Last school year we had over 600,000 users and over 2.1 million sessions!

Several of the new applets are in a recently-created Concepts category. Here we will highlight three of the new ones.

  • Simulating Sampling Distributions simplifies the layout and operation of the classic onlinestatbook applet. Users can choose from four different population shapes and explore the sampling distribution of x̄, s, and s² with various sample sizes for this lesson. You can also choose a categorical population to simulate the sampling distribution of p̂ for use with this lesson. Notice that each of the three distributions is clearly labeled and boxed, making it easier for students to distinguish the population from the sample and the sample from the sampling distribution.