1. Linear Regression and the By: Nancy Thach & Alexis Ammons July 11, 2011

2. HYPOTHESES 1.There is a correlation between the number of games a player played & total points scored. 2.There is a correlation between the age of the player & total points scored. 3.There is a correlation between the age of the player & salary. 4.There is a correlation between field goal percentage of a player & 3-point percentage. 5.There is a correlation between field goal attempts made by a player & field goal percentage.

3. Definitions A Field Goal occurs when the ball enters the basket from above during play; worth 2 points, or 3 points depending on if the shooter was standing behind the 3-point line. A 3-Point Shot is a field goal worth 3 points because the shooter had both feet on the floor behind the 3-point line when he released the ball; also counts if one foot is behind the line while the other foot is in the air.

4. Source of Data: ESPN Website: http://espn.go.com/nba/team/stats Chicago Bulls Website: http://espn.go.com/nba/team/roster

5. Number of Games Played Total Points Scored 8125 5917.5 8217.4 4811.7 828.3 807.1 816.2 824.9 824.4 524.1 133.2 822.8 62.7 181.1 21 r =.457 Weak Positive Linear Correlation Prediction: If a team member played 90 games, he would score a possible 11.2 points. y = 0.102(90) + 2.041 y = 11.2

6. Age of the Player Total Points Scored 2225 2917.5 2617.4 2611.7 308.3 267.1 266.2 274.9 314.4 384.1 233.2 252.8 322.7 331.1 281 r =.426 Weak Negative Linear Correlation Prediction: If a team member is 24 years old, it is estimated that he will score 10.8 points. y = -0.724(24) + 28.21 y = 10.8

7. Age of the PlayerSalary 225,546,160 2914,400,000 2611,345,000 263,128,536 305,000,000 261,117,680 264,790,000 273,600,000 311,600,000 381,800,000 2317,136,000 251,721,000 33854,389 28208,864 r =.369 Weak Negative Linear Correlation Prediction: If a player is 24 years old, it is estimated that he will make about $18,865,592 per year. y = -47267(24) + 2E+7 = 18,865,592

8. Field Goal Percentage 3 Point Percentage 0.4450.332 0.510 0.460.345 0.5250 0.4340.415 0.4660.125 0.480.222 0.3710.393 0.4040.38 0.5111 0.4150.222 0.5530 0.5450.571 0.5260 0.3330 r =.008 Extremely weak positive correlation; line is almost horizontal. Prediction: If a player has a field goal percentage of 0.35 = 35%, then his 3 - Point Percentage is estimated to be 0.263 = 26.3%. y = 0.031(0.35) + 0.252 =.263

9. Field Goal Attempts Field Goal Percentage 19.70.445 14.30.51 14.10.46 8.40.525 6.80.434 6.30.466 5.30.48 4.80.371 3.70.404 3.60.511 3.20.415 1.70.553 1.80.545 1.10.526 1.50.333 r =.006 Extremely weak positive correlation; line is almost horizontal. Prediction: If a player makes 20 Field Goal attempts, then his field goal percentage would be.465 = 46.5%. y = 0.00007(20) + 0.464 =.465

10. Conclusions 1.As the number of games played increases, the total number of points a player scores increases. The correlation is weak. 2.As age increases, the total number of points that he scores decreases. The correlation is weak. 3.As age increases, salary decreases. The correlation is weak. 4.As field goal percentage increases, 3-point percentage is almost constant. The correlation is extremely weak. 5.As field goal attempts increases, field goal percentage is almost constant. The correlation is extremely weak.