Amir Poat
Golden State Warriors Stats from 2016/2017 NBA Regular Season.
The data used in this project is about the stats of the 12 players that used to play for Golden State Warriors in 2016/2017 NBA regular season and it was obtained from Statcrunch website. This obtained from the stat center of NBA that shows the players points per game, minutes per game, field goal made per game, 3pointers made per game, free throws made per game, offensive rebounds per game, assists per game, turnovers per game, field goals percentage and free throw percentage. The sample size for this data is 12. This report is made by using player minutes per game as independent variable and their point per game as the dependent.
The regression equation for this sample is points per game= 5.0492847+ 0.72798521 minutes per game with a correlation coefficient equal to 0.84738795. the linear relationship is a positive strong relationship. The coefficient of determination is 0.71806634, which indicates that 71.8% of the change in dependent variable is determined by the regression equation. There seems to be a strong regression relation between the stats so a linear regression model can be done on this data set.
The dependent variable in this data set is the players points per game and the independent variable is the their minutes per game. The sample size in this project is 12. The regression equation for this sample is points per game= 5.0492847+ 0.72798521 minutes per game with a correlation coefficient equal to 0.84738795. the linear relationship is a positive strong relationship. The coefficient of determination is 0.71806634, which indicates that 71.8% of the change in dependent variable is determined by the regression equation. There seems to be a strong positive regression relation between the stats so a linear regression model can be done on this data set.
Simple linear regression results:
Dependent Variable: PTS Independent Variable: MIN PTS = 5.0492847 + 0.72798521 MIN Sample size: 12 R (correlation coefficient) = 0.84738795 Rsq = 0.71806634 Estimate of error standard deviation: 4.7567782 Parameter estimates:
Analysis of variance table for regression model:

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Apr 20, 2018
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