Use the NBA PER data introduced in Problem 8.21 and consider the model found in part $mathrm{c}$

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Use the NBA PER data introduced in Problem  8.21 and consider the model found in part $\mathrm{c}$ of that problem. There are some potential outliers in the data (the first observation is an obvious outlier). Remove the outliers and refit the model. Did removing the outliers improve the model?


Data Form Problem 8.21

Table B.23 contains player efficiency ratings (PER) from the 2016-17 and 2017-18 NBA combine that evaluates 60 rookies hoping to be drafted by NBA teams. PER is a measure of a player's per-minute productivity that is a summation of positive contribution (such as points and assists) and minus negative ones (such as turnovers and missed field goal attempts). At the combine, the PER is computed using the factors lane agility, shuttle run time, three-quarter spring time, standing vertical leap, and maximum vertical leap. The player's position is also recorded. The five positions are point guard, small (shooting) guard, small forward/small guard, and center. The PER is hopefully and indicator of how the player will perform in his first or rookie year in the league.


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Introduction To Linear Regression Analysis

ISBN: 9781119578727

6th Edition

Authors: Douglas C. Montgomery, Elizabeth A. Peck, G. Geoffrey Vining

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