Spreadsheet Modeling & Decision Analysis: A Practical Introduction To Business Analytics, Loose-leaf Version
8th Edition
ISBN: 9781337274852
Author: Ragsdale, Cliff
Publisher: South-Western College Pub
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The Wellington company wants to develop a simple linear regression model for one of its products. Use the following 12 periods of historical data to develop the
regression equation and use it to forecast the next three periods.
Click the icon to view the historical data for the previous 12 periods.
The simple linear regression line is F₁ =
+ x₁. (Enter your responses rounded to two decimal places and include a minus sign if necessary.)
Find the forecasts for periods 13-15 based on the simple linear regression and fill in the table below (enter your responses rounded to two decimal places).
Period
Forecast
(Ft)
Period
(x)
1
2
3
4
5
6
7
8
9
10
11
12
(y)
905
930
825
774
791
647
656
661
479
669
494
441
X
(x) Fo
13
14
15
Answer in Excel:
Consider the data below for the sales of widgets: 1. Using seasonal percentages or seasonal indexes, forecast the sales for each season in year 4, if the annual widgets sales is predicted to be 1500. 2. Develop a regression equation that captures both the trend and seasonality in this data. Use this equation to forecast the sales for each season in year 4.
Season
Year 1
Year 2
Year 3
Fall
505
240
210
Winter
555
460
365
Spring
400
310
204
Summer
560
450
394
Create a line graph for this set of monthly sales numbers.
Run a regression analysis.
What is the regression equation?
Is the regression equation significant? How can you tell?
What is the Rsquare? What does this signify?
What is the sales forecast for month 13?
1
550
2
548
3
546
4
549
5
550
6
548
7
551
8
551
9
552
10
551
11
553
12
553
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