DEPARTMENT. Multiple regression is used by accountants n cost analysis to shed light on the factors that cause costs o be incurred and the magnitudes of their effects. ometimes, it is desirable to use physical units instead of ost as the dependent variable in a cost analysis (e.g., if the ost associated with the activity of interest is a function of ome physical unit, such as hours of labor). The advantage f this approach is that the regression model will provide stimates of the number of labor hours required under dif- erent circumstances, and these hours can then be costed at he current labor rate (Horngren and Datar, Cost ■ccounting, 2014). The sample data shown in the table bove have been collected from a firm's accounting and roduction records to provide cost information about the rm's shipping department. These data are saved in the file. Consider the model
DEPARTMENT. Multiple regression is used by accountants n cost analysis to shed light on the factors that cause costs o be incurred and the magnitudes of their effects. ometimes, it is desirable to use physical units instead of ost as the dependent variable in a cost analysis (e.g., if the ost associated with the activity of interest is a function of ome physical unit, such as hours of labor). The advantage f this approach is that the regression model will provide stimates of the number of labor hours required under dif- erent circumstances, and these hours can then be costed at he current labor rate (Horngren and Datar, Cost ■ccounting, 2014). The sample data shown in the table bove have been collected from a firm's accounting and roduction records to provide cost information about the rm's shipping department. These data are saved in the file. Consider the model
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
Please do b, c, and d
Transcribed Image Text:Regression Analysis: Labor versus Pounds, PctShip, AveWt
Regression Equation
Labor = 131.9 +2.73 Pounds + 0.0472 PctShip - 2.587 AveWt
Coefficients
Term
Coef SE Coef T-Value P-Value VIF
Constant 131.9
25.7
Pounds
2.28
2.73
PctShip 0.0472 0.0933
AveWt
-2.587 0.643
Model Summary
9.81035 77.01%
S R-sq R-sq(adj) R-sq(pred)
72.70%
63.04%
5.13 0.000
1.20
0.248 2.25
0.51
0.620 1.09
-4.03 0.001 2.17
Analysis of Variance
Source
DF Adj SS
Regression 3 5158.31
Pounds
1 138.19
Adj MS F-Value P-Value
1719.44 17.87 0.000
138.19 1.44 0.248
1
24.62
24.62
0.26
0.620
1 1559.32 1559.32
16.20
0.001
16 1539.89
96.24
19 6698.20
PctShip
AveWt
Error
Total
Fits and Diagnostics for Unusual Observations
Fit Resid Std Resid
Obs Labor
13 50.00 73.33 -23.33
R Large residual
-2.59 R
Transcribed Image Text:DEPARTMENT. Multiple regression is used by accountants
in cost analysis to shed light on the factors that cause costs
to be incurred and the magnitudes of their effects.
Sometimes, it is desirable to use physical units instead of
cost as the dependent variable in a cost analysis (e.g., if the
cost associated with the activity of interest is a function of
some physical unit, such as hours of labor). The advantage
of this approach is that the regression model will provide
estimates of the number of labor hours required under dif-
ferent circumstances, and these hours can then be costed at
the current labor rate (Horngren and Datar, Cost
Accounting, 2014). The sample data shown in the table
above have been collected from a firm's accounting and
production records to provide cost information about the
firm's shipping department. These data are saved in the file.
Consider the model
y = Bo + B₁x1 + B₂x2 + 3x3 + ε
a. Find the least squares prediction equation.
b. Use an F-test to investigate the usefulness of the
model specified in part a. Use a = .01 and state
your conclusion in the context of the problem.
c. Test Ho: B₂ = 0 versus Ha: B₂0 using a = .05.
What do the results of your test suggest about the
magnitude of the effects of x2 on labor costs?
d. Find R² and interpret its value in the context of the
problem.
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