Operations and Supply Chain Management The Core

60 OPERATIONS AND SUPPLY CHAIN MANAGEMENT
exhibit 3.8
Excel Regression Tool
Excel:
Forecasting
The standard error of estimate is computed from the second and last columns of Exhibit 3.7:
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​S​ yt = ​ √
​ _______________________________________________________________________
​(600 − 801.3)​ 2 ​ + ​(1,550 − 1,160.9)​ 2 ​ + ​(1,500 − 1,520.5)​ 2 ​ + ⋯ + ​(4,900 − 4,757.1)​ 2 ​
​ ​
10
​
​=
363.9
In addition to the INTERCEPT and SLOPE functions, the STEYX function calculates the standard
error estimate. Microsoft Excel also has a very powerful regression tool designed to perform these
calculations. (Note that it can also be used for moving average and exponential smoothing calculations.)
To use the tool, a table is needed that contains data relevant to the problem (see Exhibit 3.8).
The tool is part of the Data Analysis ToolPak that is accessed from the Data menu (you may need to
add this to your Data options by using the Add-In option under File → Options → Add-Ins).
To use the tool, first input the data in two columns in your spreadsheet; then access the Regression
option from the → Data menu. Next, specify the Y Range, which is B2:B13, and the time periods in
the X Range, which is A2:A13 in our example. Finally, an Output Range is specified. This is where
you would like the results of the regression analysis placed in your spreadsheet. In the example, A16
is entered. There is some information provided that goes beyond what we have covered, but what you
are looking for is the Intercept and X Variable coefficients that correspond to the intercept and slope
values in the linear equation. These are in cells B32 and B33 in Exhibit 3.8.
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