Question

In: Math

data contained in the chart below (PGA Tour website, November 1, 2012) was used to develop...

data contained in the chart below (PGA Tour website, November 1, 2012) was used to develop an estimated regression equation to predict the average number of yards per drive given the ball speed and the launch angle.

Player Club Head Speed Ball Speed Launch Angle Total Distance

Bubba Watson 124.69 184.98 8.79 309.2

Dustin Johnson 121.62 180.57 11.30 301.8

J.B. Holmes 121.33 180.00 12.97 300.6

Rory McIlroy 120.21 178.07 11.25 298.6

Charlie Beljan 122.77 180.71 9.79 296.9

Robert Garrigus 121.39 180.21 12.31 296.5

John Daly 119.07 176.70 13.13 295.9

Gary Woodland 123.80 181.59 9.54 295.6

Adam Scott 119.30 176.81 9.29 295.3

Scott Piercy 117.59 174.42 11.64 295.0

Kyle Stanley 119.51 177.02 12.59 294.5

Keegan Bradley 116.83 172.35 12.61 294.3

Martin Laird 117.74 174.88 10.41 293.5

Ryan Palmer 116.12 172.43 13.31 293.2

Scott Stallings 118.85 175.48 10.74 293.1

Jason Day 119.16 176.87 11.88 292.7

Josh Teater 115.89 171.96 11.98 292.6

Harrison Frazar 114.39 169.80 12.32 292.1

Jhonattan Vegas 122.47 180.38 9.99 291.7

Louis Oosthuizen 116.79 173.32 10.59 291.3

Troy Matteson 116.55 172.48 13.09 291.1

Edward Loar 117.69 172.53 11.53 291.0

Sean O'Hair 116.52 172.87 11.84 290.7

Seung-Yul Noh 118.35 175.08 9.89 290.0

Graham DeLaet 120.04 176.71 11.86 289.7

Troy Kelly 115.64 171.38 9.97 289.7

Angel Cabrera 119.08 176.09 9.95 289.4

Lee Westwood 117.20 173.38 9.68 289.2

Jason Kokrak 118.14 175.31 10.72 288.9

Aaron Baddeley 119.05 176.75 9.04 288.7

Bill Haas 115.55 171.27 10.57 288.7

Martin Flores 118.93 175.38 9.73 288.6

Nick Watney 118.69 175.82 9.20 288.6

Phil Mickelson 116.81 173.18 10.35 288.5

Carl Pettersson 113.85 169.03 11.11 288.2

Harris English 117.43 174.16 10.03 288.2

Boo Weekley 114.87 170.52 9.41 287.9

Bo Van Pelt 114.09 169.38 11.91 287.8

Bobby Gates 119.63 175.51 9.03 287.8

Tiger Woods 120.94 177.69 10.67 287.8

Charles Howell III 118.16 173.88 8.45 287.5

Charley Hoffman 115.76 171.17 11.31 287.5

Vijay Singh 113.75 168.32 11.71 287.4

Rickie Fowler 115.64 171.41 11.72 287.3

Davis Love III 115.21 171.09 11.25 287.1

Erik Compton 114.56 170.04 12.06 287.1

Tommy Gainey 112.94 167.58 12.25 287.0

Daniel Chopra 116.88 172.20 11.74 286.8

John Rollins 113.54 168.34 11.53 286.7

Jeff Overton 112.04 166.07 11.65 286.6

Mark Anderson 117.84 174.76 9.58 286.4

Chris Couch 119.61 174.46 9.99 286.1

Jason Dufner 112.60 167.05 11.02 286.1

John Senden 115.90 171.66 9.80 286.0

Webb Simpson 113.34 166.74 10.47 285.8

Ernie Els 113.20 168.09 12.67 285.7

Kevin Chappell 117.22 172.05 10.88 285.7

Andres Romero 115.42 171.26 10.57 285.5

Charl Schwartzel 116.89 172.76 9.38 285.5

Robert Karlsson 116.86 173.67 10.85 285.5

Bud Cauley 112.39 166.45 13.32 285.4

Jonathan Byrd 115.14 170.67 10.47 285.4

Bill Lunde 111.97 166.16 10.97 285.3

Sergio Garcia 119.13 175.35 8.28 285.3

Greg Owen 118.85 174.38 9.11 285.2

Garth Mulroy 114.82 169.78 11.89 285.1

Steve Stricker 112.22 166.29 10.89 285.1

Hunter Mahan 112.05 166.15 11.12 284.8

Matt Jones 116.29 172.23 10.15 284.8

Rory Sabbatini 112.20 166.59 11.16 284.8

Scott Brown 112.53 165.95 11.90 284.8

Brian Harman 111.08 164.87 11.35 284.7

Jimmy Walker 117.43 174.04 9.93 284.7

Ryo Ishikawa 113.55 168.13 11.43 284.7

Billy Horschel 111.19 164.38 12.11 284.3

Chris Kirk 112.79 167.15 11.78 284.0

Camilo Villegas 113.03 167.86 11.31 283.9

Roberto Castro 112.82 166.77 10.73 283.8

John Merrick 113.11 167.87 9.87 283.7

Will Claxton 111.70 165.53 10.92 283.7

D.J. Trahan 114.75 169.13 11.31 283.6

Kevin Kisner 110.97 164.10 11.60 283.6

Kevin Stadler 113.62 168.43 11.20 283.6

Kevin Streelman 115.47 169.53 10.94 283.6

Danny Lee 113.89 168.05 11.01 283.5

Mathew Goggin 112.82 167.40 11.42 283.4

Justin Rose 114.63 167.47 11.99 283.3

Daniel Summerhays 113.02 167.09 10.28 283.2

Fredrik Jacobson 113.47 166.26 9.56 283.2

Pat Perez 115.40 169.33 10.84 283.2

Roland Thatcher 112.64 166.92 12.20 283.2

Stephen Gangluff 114.55 169.97 10.35 283.2

Ben Crane 109.99 163.20 12.29 283.0

Cameron Tringale 114.76 169.63 10.78 283.0

Geoff Ogilvy 114.96 170.40 10.88 283.0

J.J. Killeen 116.26 171.08 8.23 282.9

Brendan Steele 112.26 166.28 12.02 282.8

Miguel Angel Carballo 113.62 168.60 10.16 282.7

Sang-Moon Bae 114.12 168.73 9.33 282.7

Brandt Jobe 115.70 171.65 10.69 282.6

Marc Leishman 115.52 171.26 11.24 282.2

Kyle Reifers 111.59 165.44 11.70 281.8

Tim Herron 112.73 167.17 10.60 281.6

Stewart Cink 115.95 171.13 11.20 281.4

James Driscoll 117.58 173.27 8.75 281.3

Steve Wheatcroft 109.67 162.76 11.61 281.3

Jonas Blixt 111.92 164.16 11.49 281.2

Padraig Harrington 114.92 170.53 10.47 281.2

Tommy Biershenk 109.44 162.21 12.65 281.2

Tom Gillis 113.96 167.07 9.04 281.1

Chad Campbell 112.89 167.23 9.77 281.0

John Huh 111.11 164.87 11.88 281.0

Ian Poulter 110.97 164.73 9.85 280.9

Rod Pampling 112.31 166.09 9.42 280.9

Brandt Snedeker 110.75 164.04 12.61 280.8

Jeff Maggert 106.09 157.48 13.05 280.8

Johnson Wagner 110.58 164.09 10.31 280.8

Matt Every 113.42 167.54 10.98 280.8

Derek Lamely 116.06 172.10 10.75 280.6

Blake Adams 113.65 168.14 10.04 280.5

D.A. Points 110.48 163.95 11.40 280.5

Billy Mayfair 110.08 163.34 13.37 280.4

Matt Bettencourt 113.05 167.89 11.39 280.3

K.J. Choi 109.62 162.04 10.75 280.2

Brendon de Jonge 115.65 170.32 8.57 280.1

Graeme McDowell 112.40 165.25 10.04 280.0

Hunter Haas 111.96 165.31 8.51 280.0

Matt Kuchar 108.13 160.51 11.36 280.0

Ryan Moore 111.51 165.08 10.22 280.0

Robert Allenby 111.62 165.58 11.79 279.9

Marco Dawson 111.22 164.84 10.66 279.8

Ricky Barnes 116.05 170.84 8.44 279.7

Trevor Immelman 118.20 172.33 6.72 279.7

Spencer Levin 110.50 164.05 9.77 279.4

Vaughn Taylor 108.42 161.00 13.30 279.4

George McNeill 115.66 171.40 9.74 279.2

J.J. Henry 114.03 168.60 11.15 279.1

David Hearn 109.74 162.69 14.06 279.0

Y.E. Yang 112.73 166.05 9.38 278.8

Richard H. Lee 109.79 162.97 10.73 278.7

Ted Potter, Jr. 109.70 161.75 9.77 278.7

William McGirt 112.89 167.43 9.80 278.7

Cameron Beckman 109.79 162.39 10.88 278.3

Chris Stroud 111.16 164.80 10.85 278.1

Arjun Atwal 109.72 162.87 11.23 277.8

Kris Blanks 112.19 164.63 10.34 277.7

Alexandre Rocha 109.32 162.34 11.78 277.3

Chez Reavie 109.86 163.06 11.78 277.3

Kevin Na 112.97 165.33 10.04 277.3

Russell Knox 109.50 162.41 10.82 277.2

Kyle Thompson 107.68 159.89 11.65 277.1

Charlie Wi 111.44 164.82 11.15 276.9

Scott Dunlap 110.76 162.39 10.19 276.4

Zach Johnson 107.57 159.21 12.29 276.4

Stuart Appleby 112.43 165.42 9.24 276.3

Brendon Todd 110.66 163.73 10.69 276.2

Sung Kang 109.76 162.70 11.81 276.1

Michael Thompson 111.63 165.53 11.93 276.0

Jim Furyk 109.60 162.12 9.56 275.9

Dicky Pride 109.35 162.21 11.13 275.7

Nathan Green 115.02 169.92 7.63 275.6

Rocco Mediate 107.57 159.75 11.74 275.6

Gary Christian 109.31 162.23 10.54 275.3

Ben Curtis 108.23 160.08 12.00 275.2

Ken Duke 110.93 164.09 8.66 275.2

Tim Clark 104.37 154.88 12.37 275.2

Bob Estes 111.90 165.98 10.02 275.1

Michael Bradley 114.15 169.53 10.24 275.1

David Toms 104.29 154.98 13.99 274.9

Heath Slocum 106.18 157.45 11.72 274.9

Stephen Ames 109.85 161.89 10.38 274.9

Luke Donald 110.69 163.94 11.45 274.7

Patrick Sheehan 107.82 159.98 11.12 274.7

Greg Chalmers 109.83 162.54 9.29 274.6

Jason Bohn 109.76 162.83 10.33 274.4

Brian Davis 105.83 156.96 12.09 274.2

David Mathis 107.65 159.39 10.82 274.1

Justin Leonard 107.33 159.25 11.02 273.5

Bryce Molder 109.28 161.82 10.70 273.0

Mark Wilson 107.55 159.14 12.75 273.0

Brian Gary 104.59 155.17 13.09 272.8

John Mallinger 107.99 160.27 11.66 272.4

Billy Hurley III 109.15 158.94 10.26 270.9

Ryuji Imada 109.89 162.56 10.37 270.9

Jerry Kelly 105.40 155.50 12.64 270.4

Chris DiMarco 107.13 157.41 11.35 270.1

Colt Knost 106.76 157.74 10.76 268.8

Gavin Coles 104.75 154.43 10.55 268.5

Tom Pernice Jr. 107.03 158.41 11.54 268.2

Nick O'Hern 104.66 155.27 11.54 265.7

1Does the estimated regression equation provide a good fit to the data? Explain.

2 In part (b) of a different question , an estimated regression equation was developed using only ball speed to predict the average number of yards per drive. Compare the fit obtained using just ball speed to the fit obtained using ball speed and the launch angle.

Solutions

Expert Solution

Sol:

Install analysis tool apck in regression

go to data >data analysis>regression

you will get

SUMMARY OUTPUT
Regression Statistics
Multiple R 0.909863463
R Square 0.827851522
Adjusted R Square 0.826010362
Standard Error 2.848721026
Observations 190
ANOVA
df SS MS F Significance F
Regression 2 7297.779 3648.89 449.6358 3.60536E-72
Residual 187 1517.545 8.115211
Total 189 8815.324
Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Intercept 81.59638703 6.952834 11.7357 3.46E-24 67.88031532 95.31246
Ball Speed 1.092659468 0.036437 29.98778 2.31E-73 1.020779409 1.16454
Launch Angle 1.646453663 0.176476 9.329625 3.1E-17 1.298314256 1.994593

regression eq is

total distance=81.596+1.093*ballspeed+1.646*launchangle

R sq=0.8278

82.78% variation is total distance is explained by model.Good model.

F(2,187)=449.64

p=0.0000

p<0.05

Model is significant .we can use model for predicting average distance

2 In part (b) of a different question , an estimated regression equation was developed using only ball speed to predict the average number of yards per drive. Compare the fit obtained using just ball speed to the fit obtained using ball speed and the launch angle.

Now y=

total distance

x=launch angle

you will get

SUMMARY OUTPUT
Regression Statistics
Multiple R 0.002092
R Square 4.38E-06
Adjusted R Square -0.00531
Standard Error 6.847614
Observations 190
ANOVA
df SS MS F Significance F
Regression 1 0.038593 0.038593 0.000823 0.977143
Residual 188 8815.285 46.88981
Total 189 8815.324
Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Intercept 282.6682 4.421338 63.93272 1.7E-129 273.9464 291.39
Launch Angle 0.011575 0.403454 0.028689 0.977143 -0.7843 0.807454

total distance=282.668+0.012*launch angle

R sq=

R Square 4.38E-06

F(1,188)=0.0008

p=0.9777

p>0.05

Model is not significant.

R sq is less with only launch angle as predictor.

Not a good model.


Related Solutions

Develop a Gantt Chart based on Table below. On the same Gantt chart, use a legend...
Develop a Gantt Chart based on Table below. On the same Gantt chart, use a legend to show the project plan and the (actual) project progress. Discuss the significance of the two paths or what they mean to the project. Activity immediate predecessors normal time budget organizational unit percent complete A - 4 $90 U1 100 B A 2 $35 U2 100 C A 6 $75 U2 40 D B 3 $60 U1 80 E C 10 $80 U1 0...
Prepare an extended accounting equation from the below mentioned information: On November 1, 2012, Chris Clark...
Prepare an extended accounting equation from the below mentioned information: On November 1, 2012, Chris Clark deposits AED25,000 in a bank account in the name of Net Solutions. On November 5, 2012, Net Solutions agreed to pay AED20,000 for the purchase of land as a future building site. On November 10, 2012, Net Solutions purchased inventory for AED1,350 and agreed to pay the supplier in the near future. On November 18, 2012, Net Solutions received cash of AED7,500 for providing...
1. What is the UCL for the XBar chart based on the data below, with n=4,...
1. What is the UCL for the XBar chart based on the data below, with n=4, and ten set of samples for the weight of soft drinks are given. USL for the product is 355 g and LSL is 345. Daily production is 15000 units. Sample # Observations 1 352 348 350 351 2 351 352 351 350 3 351 346 342 350 4 349 353 352 352 5 351 350 351 351 6 353 351 346 346 7 348...
Morningstar publishes ratings data on 1208 company stocks (Morningstar website, October 24, 2012). A sample of...
Morningstar publishes ratings data on 1208 company stocks (Morningstar website, October 24, 2012). A sample of 40 of these stocks is contained in the WEBfile named Morningstar. Use the Morningstar data set to answer the following questions. A. Develop a point estimate of the proportion of the stocks that receive Morningstar’s highest rating of 5 Stars. b. Develop a point estimate of the proportion of the Morningstar stocks that are rated Above Average with respect to business risk. c. Develop...
Consider the following data for November 2012 from Gray Manufacturing Company, which makes silk pennants and...
Consider the following data for November 2012 from Gray Manufacturing Company, which makes silk pennants and uses a process- costing system.  All direct materials are added at the beginning of the process, and conversion costs are added evenly during the process. Spoilage is detected upon inspection at the completion of the process.  Spoiled units are disposed of at zero net disposal value.  Gray Manufacturing Company uses the FIFO method. Physical units                Direct               Conversion   (Pennants)                  Materials                 Costs                         Work in process, November 1[a]                           1000                             $1,423                $1,110 Started in November 2012                                 ? Good units...
Use the chart of data below to answer the following questions. This data represents enrollment for...
Use the chart of data below to answer the following questions. This data represents enrollment for the Fall semesters 2013 – 2017 years. Part a: Is being part time dependent upon gender? Part b: Is the probability of being a male student enrolled (or female) dependent upon year? Part c: Create a probability tree, with the appropriate probabilities using the data from the table. Assume the tree is showing the PT or FT probabilities given the gender of the student....
DATA SECTION: For the Month Ended November 30, 2017 Balance Balance November 1 November 30 Raw...
DATA SECTION: For the Month Ended November 30, 2017 Balance Balance November 1 November 30 Raw Material Inventory $ 5,600 $ 4,100 Work in Process Inventory 10,200 12,800 Finished Goods Inventory     8,100     6,700 Purchases of Raw Materials $63,000 Direct Manufacturing Labor 15,000 Indirect Manufacturing Labor 32,000 Plant Insurance     8,000 Depreciation Expense - Plant, Building, and Equip. 22,000 Repairs and Maintenance - Plant     7,200 Marketing, Distribution, and Customer-Service Costs 24,000 General and Administrative Costs 19,200 Revenue 258,300...
Below is selected data of Pronto Company: Balance Sheet Data As of December 31: 2012 2011...
Below is selected data of Pronto Company: Balance Sheet Data As of December 31: 2012 2011 Accounts receivable $671,000 $642,000 Allowance for doubtful accounts     31,000     22,000 Net accounts receivable $640,000 $620,000 Inventories - LCM $542,500 $642,500 Income Statement Data Net credit sales $3,150,000 $3,000,000 Net cash sales      800,000      600,000 Net sales $3,950,000 $3,600,000 Cost of goods sold $2,390,000 $2,160,000 Selling, general and adm. expenses 475,000 350,000 Other 150,000 125,000 Total operating expenses $3,015,000 $2,635,000 Net income...
Question 1- The Chart of Accounts is a list of accounts used by the company. The...
Question 1- The Chart of Accounts is a list of accounts used by the company. The accounts can be grouped into different categories. Using the list provided indicate the QuickBooks Account Type for each of the following accounts appearing in Craig’s Chart of Accounts Bank       Account Receivable       Other Current Assets       Fixed Assets Accounts Payable       Credit Card       Other Current Liabilities       Equity   Income       Cost of Goods Sold       Expenses       Other Income       Other Expenses...
Consider the data contained in the table below, which lists 30 monthly excess returns to two...
Consider the data contained in the table below, which lists 30 monthly excess returns to two different actively managed stock portfolios (A and B) and three different common risk factors (1, 2, and 3). (Note: You may find it useful to use a computer spreadsheet program such as Microsoft Excel to calculate your answers.) Period Portfolio A Portfolio B Factor 1 Factor 2 Factor 3 1 1.00 % 0.00 % 0.02 % -0.99 % -1.73 % 2 7.52 6.61 6.85...
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT