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The owner of a moving company wants an accurate method to predict the total number of labor hours that will be required to complete upcoming moves. The owner has decided to use the number of cubic feet moved and whether there is an elevator in the apartment building as the independent variables and has collected data for 36 moves. Use the data set given below to complete parts (a) through (n). For parts (a) through (k), do not include an interaction term. a. State the multiple regression equation that predicts labor hours, using the number of cubic feet moved, X₁, and whether there is an elevator, X₂. Define X₂ to be 0 when there is no elevator (No) and define X₂ to be 1 when there is an elevator (Yes). ŷ₁ = + (X₁₁ + (XX₂i (Round to three decimal places as needed.) b. Interpret the regression coefficients in (a). Holding constant whether there is an elevator, for each increase of 1 cubic foot moved, the predicted number of labor hours is estimated to increase by. Holding constant the number of cubic feet moved, the presence of an elevator is expected to decrease the predicted number of labor hours by

The owner of a moving company wants an accurate method to predict the total number of labor hours that will be required to complete upcoming moves. The owner has decided to use the number of cubic feet moved and whether there is an elevator in the apartment building as the independent variables and has collected data for 36 moves. Use the data set given below to complete parts (a) through (n). For parts (a) through (k), do not include an interaction term. a. State the multiple regression equation that predicts labor hours, using the number of cubic feet moved, X₁, and whether there is an elevator, X₂. Define X₂ to be 0 when there is no elevator (No) and define X₂ to be 1 when there is an elevator (Yes). ŷ₁ = + (X₁₁ + (XX₂i (Round to three decimal places as needed.) b. Interpret the regression coefficients in (a). Holding constant whether there is an elevator, for each increase of 1 cubic foot moved, the predicted number of labor hours is estimated to increase by. Holding constant the number of cubic feet moved, the presence of an elevator is expected to decrease the predicted number of labor hours by

Algebra & Trigonometry with Analytic Geometry
Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter3: Functions And Graphs
Section3.3: Lines
Problem 76E
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Include TSTAT and PVALUE 

 

Hours    Cubic Feet    Elevator
28.00    546    No
19.50    402    No
26.25    564    No
25.00    549    No
9.00    213    Yes
20.00    338    Yes
21.00    559    Yes
11.25    338    Yes
40.00    900    Yes
12.00    280    Yes
33.75    855    Yes
40.00    830    Yes
19.50    338    Yes
24.00    362    No
31.00    754    No
29.00    658    No
24.00    421    No
11.00    273    Yes
23.00    557    Yes
45.00    1027    Yes
29.00    789    Yes
28.00    529    No
18.00    563    Yes
13.50    312    Yes
37.00    761    No
35.00    602    No
34.00    789    Yes
25.00    569    Yes
31.00    494    Yes
29.00    698    No
40.00    1050    Yes
27.00    483    Yes
13.00    432    Yes
65.50    1252    No
48.75    986    Yes
79.50    1398    No

The owner of a moving company wants an accurate method to predict the total number of labor hours that will be required to complete upcoming moves. The owner has decided to use the number of cubic feet moved and whether there is an elevator in the apartment building as the independent variables and has collected data for 36 moves. Use the data set given below to complete parts (a) through (n). For parts (a) through (k), do not include an interaction term. a. State the multiple regression equation that predicts labor hours, using the number of cubic feet moved, X₁, and whether there is an elevator, X₂. Define X₂ to be 0 when there is no elevator (No) and define X₂ to be 1 when there is an elevator (Yes). ₁=+₁₁+X₂i (Round to three decimal places as needed.) b. Interpret the regression coefficients in (a). Holding constant whether there is an elevator, for each increase of 1 cubic foot moved, the predicted number of labor hours is estimated to increase by. Holding constant the number of cubic feet moved, the presence of an elevator is expected to decrease the predicted number of labor hours by
Transcribed Image Text:The owner of a moving company wants an accurate method to predict the total number of labor hours that will be required to complete upcoming moves. The owner has decided to use the number of cubic feet moved and whether there is an elevator in the apartment building as the independent variables and has collected data for 36 moves. Use the data set given below to complete parts (a) through (n). For parts (a) through (k), do not include an interaction term. a. State the multiple regression equation that predicts labor hours, using the number of cubic feet moved, X₁, and whether there is an elevator, X₂. Define X₂ to be 0 when there is no elevator (No) and define X₂ to be 1 when there is an elevator (Yes). ₁=+₁₁+X₂i (Round to three decimal places as needed.) b. Interpret the regression coefficients in (a). Holding constant whether there is an elevator, for each increase of 1 cubic foot moved, the predicted number of labor hours is estimated to increase by. Holding constant the number of cubic feet moved, the presence of an elevator is expected to decrease the predicted number of labor hours by
State the multiple regression equation that predicts the selling price, based on number of cubic feet moved, X₁, whether there is an elevator in the apartment building, X₂, and the interaction term, X3 =X₁XX₂. Ŷ₁ = + X₁ + X₂i + (X3i (Round to three decimal places as needed.) Test the interaction term. Determine the null and alternative hypotheses. Ho: B3 H₁: B3 0 0 The test statistic for the interaction term is tSTAT = 1
Transcribed Image Text:State the multiple regression equation that predicts the selling price, based on number of cubic feet moved, X₁, whether there is an elevator in the apartment building, X₂, and the interaction term, X3 =X₁XX₂. Ŷ₁ = + X₁ + X₂i + (X3i (Round to three decimal places as needed.) Test the interaction term. Determine the null and alternative hypotheses. Ho: B3 H₁: B3 0 0 The test statistic for the interaction term is tSTAT = 1
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