We want to predict the record time for women in a Scottish Hill Climb race. There are two x variables to choose from, Distance and Climb. Here is the information for the 3 dimensional relationship between x1, x2, and Y. Multinle Linear Rolati

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We want to predict the record time for women in a Scottish Hill Climb race. There are two x
variables to choose from, Distance and Climb.
Here is the information for the 3 dimensional relationship between x1, x2, and Y.
Multiple Linear Relationship for the women:
Coefficients:
Term
Coef
SE Coef
T-Value P-Value
Constant
-11.70
1.91
-6.11
0.000
Distance(km)
4.432
0.222
20.01
0.000
Climb (m)
0.04526
0.00334
13.56
0.000
Model Summary:
R-sq
R-sq(adj)
R-sq(pred)
10.1208
96.72%
96.65%
96.09%
We are asked to carry out the hypothesis tests for the net regression coefficients using the
information above. What is your decision and reason for the decision for the hypothesis test for the
X variable “Distance(km)?"
Transcribed Image Text:We want to predict the record time for women in a Scottish Hill Climb race. There are two x variables to choose from, Distance and Climb. Here is the information for the 3 dimensional relationship between x1, x2, and Y. Multiple Linear Relationship for the women: Coefficients: Term Coef SE Coef T-Value P-Value Constant -11.70 1.91 -6.11 0.000 Distance(km) 4.432 0.222 20.01 0.000 Climb (m) 0.04526 0.00334 13.56 0.000 Model Summary: R-sq R-sq(adj) R-sq(pred) 10.1208 96.72% 96.65% 96.09% We are asked to carry out the hypothesis tests for the net regression coefficients using the information above. What is your decision and reason for the decision for the hypothesis test for the X variable “Distance(km)?"
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