Chapter 6
Managerial Accounting
Linear Regression
Using Excel® 2010
Prepared by Diane Tanner
University of North Florida
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Linear Regression
 One of several cost estimation methods
 Used by managers to predict costs at various
activity levels
 More accurate than other estimation methods
 Because it uses all the data points
 Fits a total cost line through the ‘best-fit’
data points
Goal = create a cost equation
TC = FC + VCx
Y = mx + b
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How to Run a Regression in Excel 2010®
Step 1: Acquire cost information for all data points
Step 2: Be sure the Data Analysis tools are installed
Step 3: Click [Data] [Data Analysis] [Regression]
Step 4: Select the total cost data for the ‘Y’ range.
Step 5: Select the activity data for the ‘X’ range.
Step 6: Designate the cell in which you want the
regression to be placed in the output range.
Note that Excel® will extend the regression
beneath and to the right of the cell you choose.
Excel generates output that uses all the data points.
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Regression Using Excel
Example:
Given the cost and sales data
for Mix, Inc. use regression
analysis in Excel® to determine
the regression equation:
Cost
$60,000
$65,000
$73,000
$102,000
$108,000
Sales
$120,000
$132,000
$168,000
$210,000
$235,000
Step 1: Type the data into Excel®.
Step 2: Assume the Data Analysis ToolPak is
already installed.
Step 3: Click [Data] [Data Analysis] [Regression]
Step 4: Select the total cost data for the Y range.
Step 5: Select the activity data for the X range.
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Regression Using Excel
Step 6: Designate the cell in which you want the
regression to be placed in the output range. Press OK.
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.983352421
R Square
0.966981985
Adjusted R Square
Standard Error
Observations
Cost function
y = 0.44X + 5,841
0.955975979
4607.904631
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ANOVA
df
Regression
Residual
Total
Intercept
X Variable 1
SS
MS
F
Signific. F
1 1.87E+09 1.87E+09 87.85949 0.002572
3 63698355 21232785
4 1.93E+09
Standard
Lower
Upper
Coefficients
Error
t Stat
P-value Lower 95% Upper 95% 95.0%
95.0%
5841.365132 8340.922 0.700326 0.53415 -20703.2 32385.9 -20703.2 32385.9
0.437911184 0.046719 9.373339 0.002572 0.289231 0.586591 0.289231 0.586591
The End
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