How can we find value where nobody else can see it?
Learning objectives, requirement tasks, and mastery assessments
- Use linear regression to describe patterns linking two quantitative variables.
- Mastery quiz:
- Identify association and correlation in a scatterplot.
- Use StatKey to calculate the line of best fit and correlation
- Explain the slope and y-intercept of a line with proper units
- Find and explain r2
- Understand the effect of outliers and influential points on the regression line
- Predict new values using interpolation and extrapolation with the regression line. Understand each of their limitations.
- Mastery free-response questions:
- The purpose of intercepts in regression
- Multiple regression
- Non-linear transformations
- Use inference with a best-fit line to quantify confidence.
- Mastery quiz:
- Find a confidence interval of the slope
- Describe in a sentence
- Find the p-value for a test that the slope in not zero
- In a team, use multiple regression and spreadsheets to estimate Ultimate Frisbee player value and draft a winning team.
- Watch the movie Moneyball
- Learn the game Ultimate Frisbee by playing and observing
- Gain insight into player valuation from playing
- Run multiple regression on multiple statistics, and create your own stats
- Rank players
- Mastery reflection questions:
- Discuss how you used your intuition and understanding of the game and how you also used pure statistical analysis to best identify talent.
- Talk about how you approached spreadsheets with over 50,000 cells in a way that left you informed for the draft. You can draw on the days we played Ultimate, watched Moneyball, and worked as teams on the formula/graphs.
- Reference the article discussion (Billion Dollar Beane) to explain why this process is so incredibly valuable in any industry where you are searching for talent.