Please be aware that COVID-19 can be a very sensitive subject for some students and be prepared to provide these students with additional support if they need it.
These materials include content that is related to the COVID-19 pandemic. They are suitable for use in an on-level Statistics or AP Statistics course, and in some cases, in a mathematics course that includes probability and statistics content. This collection includes resources developed by statistics textbook authors Daren Starnes and Josh Tabor, Barron's review book author Martin Sternstein, college professor Allan Rossman, and stats teacher Dashiell Young-Saver.
Each resource includes a description of the intended student learning outcomes. Teachers are encouraged to preview individual resources to ensure appropriateness of the subject matter and difficulty level before using them with their students.
By Daren Starnes and Martin Sternstein
In this handout, students will investigate the relationship between the change in restaurant spending in a given state and the increase in new COVID-19 cases in that state over the next three weeks using a scatterplot, correlation, and linear regression.
By Daren Starnes
In this handout, students will analyze the implications of false positive and false negative results in antibody testing for COVID-19 using tree diagrams or two-way tables, the general multiplication rule, and conditional probability.
By Josh Tabor and Allan Rossman
In this handout, students will investigate the potential benefits of batch testing for diseases like COVID-19 by using probability rules (addition, multiplication, complement) to help create the probability distribution of a discrete random variable, and expected values to determine when batch testing is advantageous.
By Josh Tabor
In this handout, students will use data from the Moderna vaccine trial to create a confidence interval for a difference in proportions and make a conclusion based on the interval. Students will then be introduced to the concept of relative risk and guided to create a confidence interval for relative risk. Note: This handout is based on the 2009 International AP Statistics Exam Investigative Task.
By Daren Starnes
In this handout, students will use a test for a difference in proportions to analyze results from a clinical trial in the United Kingdom that tested the effectiveness of dexamethasone in reducing deaths for hospitalized COVID-19 patients.
By Josh Tabor
In this handout, students translate percentages from a news article into the observed and expected number of people of each blood type who tested positive for Covid-19 in Denmark. Then students perform a chi-square test for goodness of fit to determine if the distribution of blood type for those who test positive is different from the distribution of blood type in the population.
By Dashiell Young-Saver
In this lesson, students use the principles of study design, expected value, probability, and inference for proportions to analyze what a "95% effective" vaccine really means for tackling the COVID pandemic (spoiler: 95% effective is really good).
Dangerous Denominators: Estimating Schools' COVID Case Counts (NY Times lesson page) By Dashiell Young-Saver In this lesson, students analyze misleading uses of proportions, biased sampling methods, and the difference between associative and causal claims in relation to COVID case counts at schools. Biased Sampling and Community Spread (Skew The Script lesson page) By Dashiell Young-Saver In this lesson, students analyze how biased sampling methods might distort case count estimates in NYC. Note: Other contexts are included in the lesson. The section on COVID data is part-way through the materials