Needing to measure how each factor (WAR, ERA, WHIP) effects salaries. Needing to see the probability...

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Needing to measure how each factor (WAR, ERA, WHIP) effectssalaries. Needing to see the probability an individual with ahigher WAR will also receive a larger paycheck versus a person hasa lower WHIP or ERA (these the lower the better). For example theout of the top 10 lowest WHIP 6 are in the top 33% of payed playersbecause WHIP being low is a good factor. I believe the best way toshow this would be using either t or z distribution formulas. Anyhelp would be greatly appreciated. Looking to see how the differentvariables of WAR (wins above replacement) (this being higher shouldbe a benefit when talking about pay increases), WHIP (walks plushits per inning pitched) (the lower the WHIP the better whentalking about pay increases), and ERA (earned run average) (thelower the better when talking about pay increases) effect thesalaries of the players. Needing to know which effects the pay themost and which the least and by how much percentage wise and howthis is done. Trying to show that having a higher WAR correlates toa higher salary and having a lower ERA and WHIP correlates to ahigher salary and which has a greater impact in salary. Below arethe top 30 base salaries with their average statistics to supporttheir pay.

2019 Base Salaries

WAR

WHIP

ERA

$35,000,000

3.91

1.0976

3.372

$31,500,000

5.194

1.0562

3.108

$31,000,000

4.888

0.9328

2.402

$31,000,000

2.86

1.1864

3.552

$30,262,705

7.014

0.9454

2.72

$28,000,000

5.488

0.9914

2.964

$27,000,000

5.488

0.916

1.3428

$25,000,000

0.946

1.3782

5.196

$25,000,000

3.586

1.1854

3.4

$22,500,000

2.704

1.2548

3.588

$22,000,000

2.794

1.1334

3.918

$21,210,000

3.138

1.214

3.472

$21,000,000

2.474

1.1568

3.31

$21,000,000

1.714

1.269

4.512

$20,000,000

1.714

0.52

1.2832

$20,000,000

1.76

1.2148

3.86

$20,000,000

2.804

1.2752

3.774

$18,000,000

2.804

1.532

0.8556

$18,000,000

1.418

1.2752

4.616

$18,000,000

1.534

1.0006

2.66

$18,000,000

1.534

1.528

1.1982

$17,900,000

1.846

1.3468

4.608

$17,000,000

0.962

1.3644

4.668

$17,000,000

2.538

1.2362

3.768

$17,000,000

4.772

1.1256

3.548

$16,500,000

4.772

1.196

1.303

$16,000,000

1.432

1.269

4.21

$15,250,000

2.036

1.3172

4.15

$15,000,000

4.692

1.0102

3.24

$15,000,000

4.692

1.594

1.0662

Answer & Explanation Solved by verified expert
4.1 Ratings (823 Votes)
To investigate this the first step would be to calculate the individual impact of each of the variables WAR WHIP and ERA on 2019 Base Salaries This is calculated using correlation measure to quantify the linear association between two variables and coefficient of determination proportion of variation in Salary    See Answer
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