#3) Use computer software packages, such as Excel, to solve this problem. Consid
ID: 3367261 • Letter: #
Question
#3) Use computer software packages, such as Excel, to solve this problem.
Consider the following data for 15 golfers on the LPGA in 2014. Provided is their money Earned during the year, the frequency they hit the Green in Regulation, and their consensus putting ability as voted on by their peers (grade was either given to be "Good" or "Poor").
Player
Earnings ($)
Greens in Reg.
Putter
Annika Sorenstam
2,588,240
0.772
Good
Paula Creamer
1,531,780
0.727
Good
Cristie Kerr
1,360,941
0.722
Good
Lorena Ochoa
1,201,786
0.697
Good
Jeong Jang
1,131,986
0.710
Poor
Natalie Gulbis
1,010,154
0.709
Poor
Meena Lee
870,182
0.686
Poor
Hee-Won Han
856,364
0.707
Good
Gloria Park
842,349
0.700
Poor
Catriona Matthew
776,924
0.696
Good
Candie Kung
753,959
0.702
Poor
Marisa Baena
744,679
0.684
Poor
Birdie Kim
715,006
0.679
Poor
Soo-Yun Kang
710,710
0.631
Good
Lorie Kane
698,763
0.718
Poor
Convert the Categorical Variable (Putter) into a numerical variable and develop an estimated regression equation that can be used to predict a player's Earnings for the season based their green in regulation frequency and their putting ability.
What is the p-value for the categorical variable Putter? Round to 3 decimals.
Is the Putter variable significantly adding to the model at the ? = 0.05 level?
What is the difference in Earnings between a Good putter and Poor putter, assuming their green in regulation frequencies are held constant? Round to the nearest dollar.
In 2014, golfer Stacy Lewis hit the green 75.8% of the time and was considered by her peers to be a Poor putter, however she made $2,539,039 in earnings. Would you consider that amount unusual? Use Excel to create a 95% Prediction Interval for that golfer’s expected earnings based on her statistics and compare that to her actual amount $2,539,039 to support your answer.
Player
Earnings ($)
Greens in Reg.
Putter
Annika Sorenstam
2,588,240
0.772
Good
Paula Creamer
1,531,780
0.727
Good
Cristie Kerr
1,360,941
0.722
Good
Lorena Ochoa
1,201,786
0.697
Good
Jeong Jang
1,131,986
0.710
Poor
Natalie Gulbis
1,010,154
0.709
Poor
Meena Lee
870,182
0.686
Poor
Hee-Won Han
856,364
0.707
Good
Gloria Park
842,349
0.700
Poor
Catriona Matthew
776,924
0.696
Good
Candie Kung
753,959
0.702
Poor
Marisa Baena
744,679
0.684
Poor
Birdie Kim
715,006
0.679
Poor
Soo-Yun Kang
710,710
0.631
Good
Lorie Kane
698,763
0.718
Poor
Explanation / Answer
Let use assume that the Categorical Variable (Goood, Poor) converted into a numerical variable (1,0), then, the data is change in numerical data. Using excel to solve this
The estiamted regression model is
Earnings = -7514248+11968694*Greens+336786.9*Putter
the p-value for the categorical variable Putter is 0.042064
Yes, the Putter variable is significantly adding to the model at the 0.05 level becuase the p-value is less than 0.05.
The difference in Earnings between a Good putter and Poor putter is 336786.9
If Green is 75.8% with poor putter, then earning is
Earnings = -7514248+11968694*0.758+336786.9*0 =$15,580,22
Yes the amount is given unusual
SUMMARY OUTPUT Regression Statistics Multiple R 0.849573 R Square 0.721774 Adjusted R Square 0.675403 Standard Error 282631.6 Observations 15 ANOVA df SS MS F Significance F Regression 2 2.49E+12 1.24E+12 15.56521 0.000464 Residual 12 9.59E+11 7.99E+10 Total 14 3.45E+12 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept -7514248 1787962 -4.20269 0.001226 -1.1E+07 -3618613 Greens 11968694 2555716 4.683107 0.000529 6400266 17537121 Putter 336786.9 148044.9 2.274897 0.042064 14224.71 659349.1Related Questions
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