Linear Regression: MLB example
- Ying-Ju Chen
- Linear Regression
The scatterplot shows the relationship between the number of wins in 2014 and the improvement of wins in 2015 for 15 Major League Baseball teams. The data are from https://www.teamrankings.com/mlb/trends/win_trends/.
[1.] Describe the general pattern in the scatterplot. Are teams with higher wins in 2014 more successful in 2015?
[2.] What is the explanatory variable? What is the response?
[3.] How does this pattern demonstrate Regression to the Mean?
[4.] Click the checkbox for showing the regression line. What is the equation of the regression line?
[5.] What does the slope mean in the context? What does the y-intercept mean in the context?
[6.] Click the checkbox for showing the correlation coefficient and interpret the value of .
[7.] Use the line to predict the number of Improvement in 2015 for the Chicago Cubs. Find the residual for this team.
[8.] You should find that the Chicago Cubs won 28 games in this season. Predict the team's improvement in the following season. Does it make sense to use this linear model to predict the Chicago Cubs' performance in the following season? Why?