This course is based on the 2018 AP Statistics curriculum and introduces everything from basic descriptive statistics to data collection to hot topics in data analysis like Big Data and neural networks.
Last week we introduced the ANOVA model which allows us to compare measurements of more than two groups, and today we’re going to show you how it can be applied to look at data that belong to multiple groups that overlap and interact.
Today we’re going to finish up our unit on data visualization by taking a closer look at how dot plots, box plots, and stem and leaf plots represent data.
Today we’re going to wrap up our discussion of General Linear Models (or GLMs) by taking a closer looking at two final common models: ANCOVA (Analysis of Covariance) and RMA (Repeated Measures ANOVA).
In this lesson, students use quadratic functions to develop a model of expected points, which measure how many points a team can expect to score from different field positions.
In this lesson, students analyze almost thirty years’ worth of data summarized in n-way frequency tables and discuss whether they see evidence of racial bias in who receives the death penalty and who doesn’t.