Scottish Hill Climb races  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 are the first few rows from the data table. Race                                        Men (mins)      Women(mins) Distance(km)  Climb (m) Alva Games Hill Race            18.650             25.817             2.5                   385 Aonach Mor Uphill Race        22.250            26.467             4.0                   610 Arrochar Alps                         187.650           249.433          25.0                 2400 Once you have chosen the best single x variable to predict the record time for women, does it help to add the 2nd x variable?  Here is the information for the two single x variables.  Coefficients for Distance: Term               Coef    SE Coef           T-Value            P-Value Constant         -7.15    3.32               -2.16                0.034   Distance(km)  6.765    0.246             27.55               0.000   Model Summary for Distance: S                      R-sq                 R-sq(adj)         R-sq(pred) 17.8222          89.72%            89.60%            88.19%   Coefficients for Climb: Term               Coef                SE Coef           T-Value   P-Value  Constant         2.60                 4.20                 0.62       0.538     Climb (m)        0.09717           0.00497         19.55      0.000     Model Summary for Climb: S                      R-sq                 R-sq(adj)         R-sq(pred) 23.9301          81.46%            81.25%            80.54%     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: S                          R-sq                    R-sq(adj)            R-sq(pred) 10.1208              96.72%               96.65%               96.09%    Carry out the two hypothesis tests for the net regression coefficients using the information above.   State the hypothesis you are testing.  State your decision and the reason you are making the decision.  Finally, explain what the decision means.

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Scottish Hill Climb races 

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 are the first few rows from the data table.

Race                                        Men (mins)      Women(mins) Distance(km)  Climb (m)

Alva Games Hill Race            18.650             25.817             2.5                   385

Aonach Mor Uphill Race        22.250            26.467             4.0                   610

Arrochar Alps                         187.650           249.433          25.0                 2400

Once you have chosen the best single x variable to predict the record time for women, does it help to add the 2nd x variable? 

Here is the information for the two single x variables. 

Coefficients for Distance:

Term               Coef    SE Coef           T-Value            P-Value

Constant         -7.15    3.32               -2.16                0.034  

Distance(km)  6.765    0.246             27.55               0.000  

Model Summary for Distance:

S                      R-sq                 R-sq(adj)         R-sq(pred)

17.8222          89.72%            89.60%            88.19%  

Coefficients for Climb:

Term               Coef                SE Coef           T-Value   P-Value 

Constant         2.60                 4.20                 0.62       0.538    

Climb (m)        0.09717           0.00497         19.55      0.000    

Model Summary for Climb:

S                      R-sq                 R-sq(adj)         R-sq(pred)

23.9301          81.46%            81.25%            80.54%    

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:

S                          R-sq                    R-sq(adj)            R-sq(pred)

10.1208              96.72%               96.65%               96.09%   

Carry out the two hypothesis tests for the net regression coefficients using the information above.  

State the hypothesis you are testing.  State your decision and the reason you are making the decision.  Finally, explain what the decision means.  

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