Week 5 Quiz on Regression Analysis >> Marketing Analytics
Zodiac wants to sponsor an up-and-coming golf player to endorse its watches. Using regression analysis to predict player earnings as a measure of success, they think player height and earnings might be related. Based on the graph above, what is the relationship between height and earnings–and what should Zodiac look for in a player to sponsor?
A sports management company wants to represent the most financially successful basketball players. They turn to regression analysis to identify predictors of players’ salary. Using the data plotted above, they run a regression with salary as the dependent variable and age as independent variable. What sign is the coefficient of age?
Based on the output from a regression of golf player heights and their corresponding earnings (above), what measure provides an estimate of the strength of the relationship between height and earnings?
Based on the output from a regression of golf player heights and their corresponding earnings (above), how much do earnings increase for each unit increase in height?
Based on the output from a regression of basketball player age and corresponding salary (above), how would you interpret a p-value of <.01 for the coefficient of age?
Based on the output from a regression of golf player heights and the corresponding earnings (above), what is the predicted value of earnings when height is zero?
Based on the output from a regression of basketball player age and points scored per game and corresponding salary (above), which factors predict differences in salary?
Based on the output from a regression of basketball player age, points scored per game, and corresponding salary (above), how do salaries change with improvements in points scored per game?
Based on the chart (above), what decision should a sports management agency take and what factors should they look for when pursuing new talent?
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