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Player Scoring Avg. Drive Average Greens in Reg. Putting Avg. Sand Saves DriveGr

ID: 3151750 • Letter: P

Question

Player Scoring Avg. Drive Average Greens in Reg. Putting Avg. Sand Saves DriveGreens Annika Sorenstam 69.33 263 0.772 1.75 0.595 203.036 Paula Creamer 70.98 248.6 0.727 1.75 0.468 180.732 Cristie Kerr 70.86 255.5 0.722 1.76 0.362 184.471 Lorena Ochoa 71.39 261.7 0.697 1.75 0.31 182.405 Jeong Jang 71.17 244.8 0.71 1.79 0.485 173.808 Natalie Gulbis 71.24 252.9 0.709 1.78 0.343 179.306 Meena Lee 72.32 238.2 0.686 1.82 0.422 163.405 Hee-Won Han 71.31 241.7 0.707 1.78 0.444 170.882 Gloria Park 71.43 242 0.7 1.79 0.426 169.4 Catriona Matthew 71.46 251.4 0.696 1.78 0.443 174.974 Candie Kung 71.52 247.7 0.702 1.85 0.393 173.885 Marisa Baena 71.92 251.1 0.684 1.79 0.446 171.752 Birdie Kim 73.16 240 0.679 1.86 0.386 162.96 Soo-Yun Kang 71.8 241.2 0.631 1.77 0.581 152.197 Lorie Kane 72.28 245.7 0.718 1.84 0.475 176.413 Heather Bowie 71.46 258.3 0.742 1.82 0.455 191.659 Wendy Ward 72.14 246.7 0.707 1.81 0.413 174.417 Pat Hurst 71.47 259.3 0.709 1.77 0.36 183.844 Christina Kim 71.66 254 0.718 1.82 0.307 182.372 Rosie Jones 71.58 230.9 0.662 1.8 0.435 152.856 Carin Koch 71.59 250.2 0.699 1.79 0.408 174.89 Liselotte Neumann 71.47 249.1 0.679 1.81 0.322 169.139 Mi Hyun Kim 71.65 237.4 0.674 1.8 0.25 160.008 Juli Inkster 71.33 251.2 0.701 1.79 0.375 176.091 Michele Redman 71.59 244.6 0.686 1.81 0.386 167.796 Jennifer Rosales 71.85 252.1 0.705 1.81 0.417 177.731 Karrie Webb 71.52 256.2 0.709 1.81 0.353 181.646 Sophie Gustafson 72.59 269.2 0.651 1.81 0.389 175.249 Young Kim 71.7 250.7 0.678 1.79 0.292 169.975 Karine Icher 72.13 244 0.728 1.76 0.222 177.632

Explanation / Answer

What steps in Minitab would I need to predict a player’s average score using forward, backward, and stepwise procedure? Would the estimated regression equations be identical?

Solution:

For the purpose of predicting the player’s average score using the forward, backward and stepwise procedure, we need the following Minitab steps.

Step I

First open the Minitab and paste the data in Minitab worksheet.

Step II

Click on ‘Stat’ and then select ‘Regression’ and click on the ‘Stepwise’.

Step III

In the pop-up at the below click on ‘Methods’ and then check out the field for stepwise, backward or forward regression

Step IV

Fill up all entries for variables and press ‘Ok’ to get desired results.

The forward, backward and stepwise regression for your data set by using Minitab is given as below:

—————   09/04/2015 9:35:13 AM   ————————————————————

Welcome to Minitab, press F1 for help.

Stepwise Regression: Scoring Avg. versus Drive Averag, Greens in Re, ...

Alpha-to-Enter: 0.15 Alpha-to-Remove: 0.15

Response is Scoring on 5 predictors, with N =   30

    Step          1        2        3

Constant      46.28    58.09    59.02

Putting        14.1     11.7     11.4

T-Value        4.20     4.04     4.14

P-Value       0.000    0.000    0.000

Greens i               -10.7    -10.3

T-Value                -3.56    -3.57

P-Value                0.001    0.001

Sand Sav                        -1.81

T-Value                         -1.97

P-Value                         0.060

S             0.511    0.429    0.408

R-Sq          38.67    58.26    63.67

R-Sq(adj)     36.48    55.17    59.48

C-p            28.3     12.9     10.2

Stepwise Regression: Scoring Avg. versus Drive Averag, Greens in Re, ...

Forward selection. Alpha-to-Enter: 0.25

Response is Scoring on 5 predictors, with N =   30

    Step          1        2        3

Constant      46.28    58.09    59.02

Putting        14.1     11.7     11.4

T-Value        4.20     4.04     4.14

P-Value       0.000    0.000    0.000

Greens i               -10.7    -10.3

T-Value                -3.56    -3.57

P-Value                0.001   0.001

Sand Sav                        -1.81

T-Value                         -1.97

P-Value                         0.060

S             0.511    0.429    0.408

R-Sq          38.67    58.26    63.67

R-Sq(adj)     36.48    55.17    59.48

C-p            28.3     12.9     10.2

Stepwise Regression: Scoring Avg. versus Drive Averag, Greens in Re, ...

Backward elimination. Alpha-to-Remove: 0.1

Response is Scoring on 5 predictors, with N =   30

    Step          1        2

Constant    -71.38   -88.10

Drive Av       0.52     0.59

T-Value        2.83     3.49

P-Value       0.009    0.002

Greens i        185      209

T-Value        2.70     3.33

P-Value       0.013    0.003

Putting         9.8      9.7

T-Value        3.78     3.78

P-Value       0.001    0.001

Sand Sav      -0.80        

T-Value       -0.89        

P-Value       0.384        

DriveGre      -0.77    -0.87

T-Value       -2.85    -3.50

P-Value       0.009    0.002

S             0.367    0.365

R-Sq          72.89   72.00

R-Sq(adj)     67.24    67.52

C-p             6.0      4.8

Estimated regression equations are not identical.