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 www.stapplet.com (also available at www.statsmedic.com/applets). If you haven't been to www.stapplet.com 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.
Simulating Confidence Intervals is similar to other confidence interval applets, but has the advantage of being built from the Simulating Sampling Distributions applet. This makes it easy for students to understand what they are seeing as they explore confidence level and the factors that affect margin of error in this lesson.
The Power applet allows users to calculate—and illustrate—power for a test of a single proportion and a test of a single mean. Clicking the up/down arrows in entry boxes allow users to see impact of changing sample size, α, and effect size. There is also an option to show rejection region. Hovering over rejection region shows values of x̄ or p̂ that lead to a rejection of Ho. Perfect for this lesson.
In the world of regression, we have two new applets and at least one notable improvement. First the improvement—in the Two Quantitative Variables applet, users now have the option to get traditional computer output when calculating a linear model. This will be very helpful for generating classroom examples and writing test questions. New applets include aGuess the Correlation applet, perfect for an in-class contest. And to launch your study of inference for slope, the Old Faithful applet randomly selects points from a scatterplot to simulate the sampling distribution of the sample slope.
In the Probability category, we have added applets for the t Distributions and for the χ2 Distributions, along with a couple BAPS (Beyond AP Statistics) distributions: Poisson and F. And all of the probability calculators have been updated so users can click the up/down arrows to immediately see how these changes affect the distribution and probability calculations.
Adding to the collaborative applets described here, we now offer a collaborative version of the One Quantitative Variable, Multiple Groups applet. This applet is ideal for collecting data that results in 2 or more parallel dotplots, such as Does Beyonce Write Her Own Lyrics? or The German Tank Problem. The teacher creates a class code, sets up the variable and group names in the Teacher Panel, shares the class code, and then enables data collection.
Speaking of the collaborative applets, you can now export the data you collect into the traditional applet with a single click. This allows you to access all the appropriate inference options. We have also sped up the refresh rate on the teacher page and addressed a lingering issue where values briefly disappear when the applet updates. The refresh rate change applies to the collaborative Activity applets as well, for lessons such as How Much do Fans Like Justin Timberlake? and Is Mrs. Gallas a Good Free Throw Shooter?
Finally, we added a bunch of BAPS options in the Data Analysis applets and made several other small improvements. A detailed list of all changes is available here.
We hope that these new and improved applets will be helpful to you and your students this year. And please let us know if you have any suggestions. We listen! Just ask Doug Tyson, whose students requested more color options, Erica Chauvet, who asked for labels on normal curves, Jeff Eicher, who asked for a boxplot option when graphing a normal probability plot, and Jared Derksen, who has an affinity for Froot Loops.
Josh Tabor (TaborStats@gmail.com)
Bob Amar (bobamarmath@gmail.com)