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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.

Common Core Standards

Content Standards
Mathematical Practices

Additional Materials

  • Graphing calculators


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