The file P10_08.xlsx contains data on the top 200 professional golfers in 2017. Create a new variable, Birdies per Round, in column R. Then explore several multiple regressions for Earnings per Round, using the variables in columns I-M and R. Proceed as follows.

Create a table of correlations for these variables. Round your answers to three decimal places, if necessary. If your answer is negative number, enter "minus" sign.

Linear Correlation Table	Yards/Drive	Driving Accuracy	Greens in Regulation	Putting Average	Sand Save Pct	Birdies Per Round
Earnings Per Round

Run a regression of Earnings per Round versus the most highly correlated variable (positive or negative) with Earnings per Round. Then run a second regression with the two most highly correlated variables with Earnings per Round. Then run a third with the three most highly correlated, and so on until all six explanatory variables are in the equation.

Let X₁ represent the putting average. Let X₂ represent the yards/drive. Let X₃ represent the greens in regulation. Let X₄ represent the birdies per round. Let X₅ represent the sand save pct. Let X₆ represent the driving accuracy.

Round your answers to one decimal place, if necessary. If your answer is negative number, enter "minus" sign.

Regression of Earnings per Round with X₁:

= _____+ _______ X₁

Regression of Earnings per Round with X₁ and X₂:

= ____+____ X₁ + ____ X₂

Regression of Earnings per Round with X₁ through X₃:

= _____+_____ X₁ +______ X₂ +______ X₃

Regression of Earnings per Round with X₁ through X₄:

= _____+_____ X₁ +______ X₂ +______ X₃ + ____ X₄

Regression of Earnings per Round with X₁ through X₅:

=_____+_____ X₁ +______ X₂ +______ X₃ + ____ X₄ +_____ X₅

Regression of Earnings per Round with X₁ through X₆:

= _____+_____ X₁ +______ X₂ +______ X₃ + ____ X₄ +_____ X₅+ _____ X₆

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