Reference no: EM132860112
A manufacturer of children's tricycles is interested in estimating the relationship between its monthly factory overhead, Y (in $1000s), and the total number of tricycles, X (in 100s of units), produced per month. The estimate will be used to help develop the manufacturing budget for next year. The data below have been collected over the last 12 months:
# Tricycles, X (in 100s)
16.9
15.6
17.4
11.6
17.1
17.6
16.3
15.5
23.4
28.4
27.1
19.2
Overhead, Y (in $1000s)
41.4
35.0
38.3
29.5
39.6
37.4
37.5
37.0
47.9
55.6
53.1
40.6
A simple linear regression model was formulated. The Excel output appears below.
a) Specify the regression equation to predict overhead as a function of number of tricycles sold.
b) From the information on residuals provided, is it reasonable to conclude that the model is valid? Be specific.
c) Specify and interpret the coefficient of determination, r2
d) Set up and conduct an appropriate test for the significance of the linear relationship between # tricycles produced per month and monthly overhead, using a=0.05, and state the conclusion.
e) Specify a point estimate of the overhead for a month in which 17 hundred tricycles were produced.
f) For a particular month in which 17 hundred tricycles were produced, the actual overhead was 15 thousand dollars. Briefly, but clearly, comment on this observation.
A manufacturer of children's tricycles is interested in estimating the relationship between its monthly factory overhead, Y (in $1000s), and the total number of tricycles, X (in 100s of units), produced per month. The estimate will be used to help develop the manufacturing budget for next year. The data below have been collected over the last 12 months:
## Tricycles, X (in 100s)
16.9
15.6
17.4
11.6
17.1
17.6
16.3
15.5
23.4
28.4
27.1
19.2
Overhead, Y (in $1000s)
41.4
35.0
38.3
29.5
39.6
37.4
37.5
37.0
47.9
55.6
53.1
40.6
A simple linear regression model was formulated. The Excel output appears below.
a) Specify the regression equation to predict overhead as a function of number of tricycles sold.
b) From the information on residuals provided, is it reasonable to conclude that the model is valid? Be specific.
c) Specify and interpret the coefficient of determination, r2
d) Set up and conduct an appropriate test for the significance of the linear relationship between # tricycles produced per month and monthly overhead, using a=0.05, and state the conclusion.
e) Specify a point estimate of the overhead for a month in which 17 hundred tricycles were produced.
f) For a particular month in which 17 hundred tricycles were produced, the actual overhead was 15 thousand dollars. Briefly, but clearly, comment on this observation.
A manufacturer of children's tricycles is interested in estimating the relationship between its monthly factory overhead, Y (in $1000s), and the total number of tricycles, X (in 100s of units), produced per month. The estimate will be used to help develop the manufacturing budget for next year. The data below have been collected over the last 12 months:
# Tricycles, X (in 100s)
16.9
15.6
17.4
11.6
17.1
17.6
16.3
15.5
23.4
28.4
27.1
19.2
Overhead, Y (in $1000s)
41.4
35.0
38.3
29.5
39.6
37.4
37.5
37.0
47.9
55.6
53.1
40.6
A simple linear regression model was formulated. The Excel output appears below.
a) Specify the regression equation to predict overhead as a function of number of tricycles sold.
b) From the information on residuals provided, is it reasonable to conclude that the model is valid? Be specific.
c) Specify and interpret the coefficient of determination, r2
d) Set up and conduct an appropriate test for the significance of the linear relationship between # tricycles produced per month and monthly overhead, using a=0.05, and state the conclusion.
e) Specify a point estimate of the overhead for a month in which 17 hundred tricycles were produced.
f) For a particular month in which 17 hundred tricycles were produced, the actual overhead was 15 thousand dollars. Briefly, but clearly, comment on this observation.