It seems that certain countries are perennial powerhouses in the Winter Games. So, is there a way to use existing data to predict how many medals an individual nation will end up taking home? Two researchers think they may have found a solution.

In this lesson, students use scatterplots and linear regression to examine several variables that may help predict Olympic performance. Are the Winter Games largely decided before the opening ceremonies even start?

### Students will

• Use a scatterplot to describe the qualitative relationship between two variables
• Interpret the results of a linear regression (equation and correlation coefficient) in context
• Make predictions about Olympic performance based on regression results
• Create scatterplots and best-fit lines from tabular data using technology
• Compare regression results for various explanatory variables
• Describe the strengths and weaknesses of using simple linear regressions, and examine the predictions of a multiple regression

### Before you begin

Students should already be familiar with the basics of regression analysis, including how to use technology to generate a simple linear regression. This lesson is intended as an application of those topics, not an introduction, though it includes a brief review of interpreting scatterplots and regression equations in context.