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Build a Regression Model
-A Researcher Is Investigating Whether Exercise

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Build a Regression Model
-A researcher is investigating whether exercise, age, and percent body fat could be good predictors of resting pulse rate. She selects a random sample of women and for each woman records their resting pulse rate, the amount they exercise (on a scale of 1 to 10), age, and percent body fat. The results are shown in the table.
 Resting Pulse Rate  Amount of Exercise  Age  Percent Body Fat 766222363838198256225903543186244277744124805592675427265883516765762465931208536628\begin{array}{c|c|c|c}\text { Resting Pulse Rate } & \text { Amount of Exercise } & \text { Age } & \text { Percent Body Fat } \\\hline 76 & 6 & 22 & 23 \\63 & 8 & 38 & 19 \\82 & 5 & 62 & 25 \\90 & 3 & 54 & 31 \\86 & 2 & 44 & 27 \\77 & 4 & 41 & 24 \\80 & 5 & 59 & 26 \\75 & 4 & 27 & 26 \\58 & 8 & 35 & 16 \\76 & 5 & 76 & 24 \\65 & 9 & 31 & 20 \\85 & 3 & 66 & 28\end{array}

(a) Construct the correlation matrix. Is there any reason to be concerned with collinearity? Is this what you would expect?
(b) Find the least squares regression equation y^=b0+b1x1+b2x2+b3x3\hat { y } = b _ { 0 } + b _ { 1 } x _ { 1 } + b _ { 2 } x _ { 2 } + b _ { 3 } x _ { 3 } , where x1x _ { 1 } is Exercise, x2x _ { 2 } is Age, x3x _ { 3 } is Percent body fat, and yy is the response variable "resting pulse rate".
(c) Test H0:β1=β2=β3=0\mathrm { H } _ { 0 } : \beta _ { 1 } = \beta _ { 2 } = \beta _ { 3 } = 0 versus H1\mathrm { H } _ { 1 } : at least one of the βi0\beta _ { \mathrm { i } } \neq 0 at the α=0.05\alpha = 0.05 level of significance.
(d) Test the hypotheses H0:β1=0\mathrm { H } _ { 0 } : \beta _ { 1 } = 0 versus H1:β10,H0:β2=0\mathrm { H } _ { 1 } : \beta _ { 1 } \neq 0 , \mathrm { H } _ { 0 } : \beta _ { 2 } = 0 versus H1:β20\mathrm { H } _ { 1 } : \beta _ { 2 } \neq 0 , and H0:β3=0\mathrm { H } _ { 0 } : \beta _ { 3 } = 0 versus H1\mathrm { H } _ { 1 } : β30\beta _ { 3 } \neq 0 at the α=0.05\alpha = 0.05 level of significance.
Should any of the explanatory variables be removed from the model? If so, which one? Why?
(e) Determine the least squares regression equation with the explanatory variable identified in part (d) removed.
(f) Are both slope coefficients significantly different from zero? Is this what you would expect? If appropriate, remove an explanatory variable and compute the new least squares regression equation.
(g) What is the P-value for your final regression equation? What does this imply?


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Agreed-upon guidelines that dictate the behavior expected of individuals within a society or group.

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Established norms, rules, or practices that dictate certain behaviors or actions within a society or group.

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A biased belief that differences in cultural or individual characteristics are inherently inferior.

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