Modern Business Statistics with Microsoft Excel (MindTap Course List)
5th Edition
ISBN: 9781285433301
Author: David R. Anderson, Dennis J. Sweeney, Thomas A. Williams
Publisher: Cengage Learning
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Textbook Question
Chapter 17.5, Problem 30E
The quarterly sales data (number of copies sold) for a college textbook over the past three years follow.
- a. Construct a time series plot. What type of pattern exists in the data?
- b. Use the following dummy variables to develop an estimated regression equation to account for any seasonal effects in the data: Qtr1 = 1 if Quarter 1, 0 otherwise; Qtr2 = 1 if Quarter 2, 0 otherwise; Qtr3 = 1 if Quarter 3, 0 otherwise.
- c. Compute the quarterly forecasts for next year.
- d. Let t = 1 to refer to the observation in quarter 1 of year 1; t = 2 to refer to the observation in quarter 2 of year 1; … and t = 12 to refer to the observation in quarter 4 of year 3. Using the dummy variables defined in part (b) and t, develop an estimated regression equation to account for seasonal effects and any linear trend in the time series. Based upon the seasonal effects in the data and linear trend, compute the quarterly forecasts for next year.
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Consider the following time series data.
Quarter Year 1 Year 2 Year 3
1 4 6 7
2 2 3 6
3 3 5 6
4 5 7 8
Choose the correct time series plot.
(i)
(ii)
(iii)
(iv)
- Plot (iii) What type of pattern exists in the data?- Horizontal Pattern with Seasonality
Use a multiple regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data. Qtr1 = 1 if Quarter 1, 0 otherwise; Qtr2 = 1 if Quarter 2, 0 otherwise; Qtr3 = 1 if Quarter 3, 0 otherwise. If required, round your answers to three decimal places. For subtractive or negative numbers use a minus sign even if there is a + sign before the blank. (Example: -300)Value = fill in the blank 3 + fill in the blank 4 Qtr1 + fill in the blank 5 Qtr2 + fill in the blank 6 Qtr3 + fill in the blank 7 t
Compute the quarterly forecasts for next year. If…
Consider the following time series:
Quarter
Year 1
Year 2
Year 3
1
66
63
57
2
48
40
50
3
59
61
54
4
73
76
67
(a)
Choose a time series plot.
(i)
(ii)
(iii)
(iv)
What type of pattern exists in the data? Is there an indication of a seasonal pattern?
(b)
Use a multiple linear regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data: Qtr1 = 1 if quarter 1, 0 otherwise; Qtr2 = 1 if quarter 2, 0 otherwise; Qtr3 = 1 if quarter 3, 0 otherwise. For subtractive or negative numbers use a minus sign even if there is a + sign before the blank (Example: -300).
ŷ = ?? + ?? Qtr1 +?? Qtr2 + ?? Qtr3
(c)
Compute the quarterly forecasts for next year.
Year
Quarter
Ft
4
1
4
2
4
3
4
4
Which of the following time-series forecasting methods would not be used to forecast a time series that exhibits a linear trend with no seasonal or cyclical patterns?
a. Dummy variable regression
b. Linear trend regression
c. Multiplicative Winter's method
d. Holt Winter's double exponential smoothing
e. Both A and D
Chapter 17 Solutions
Modern Business Statistics with Microsoft Excel (MindTap Course List)
Ch. 17.2 - 1. Consider the following time series...Ch. 17.2 - 2. Refer to the time series data in exercise 1....Ch. 17.2 - Prob. 3ECh. 17.2 - 4. Consider the following time series...Ch. 17.3 - Consider the following time series...Ch. 17.3 - Consider the following time series...Ch. 17.3 - Refer to the gasoline sales time series data in...Ch. 17.3 - Prob. 8ECh. 17.3 - 9. With the gasoline time series data from Table...Ch. 17.3 - 10. With a smoothing constant of α = .2, equation...
Ch. 17.3 - For the Hawkins Company, the monthly percentages...Ch. 17.3 - Corporate triple-A bond interest rates for 12...Ch. 17.3 - The values of Alabama building contracts (in $...Ch. 17.3 - The following time series shows the sales of a...Ch. 17.3 - Ten weeks of data on the Commodity Futures Index...Ch. 17.3 - Prob. 16ECh. 17.4 - Consider the following time series...Ch. 17.4 - Prob. 18ECh. 17.4 - Prob. 19ECh. 17.4 - Prob. 20ECh. 17.4 - Prob. 21ECh. 17.4 - Prob. 22ECh. 17.4 - The president of a small manufacturing firm is...Ch. 17.4 - FRED (Federal Reserve Economic Data), a database...Ch. 17.4 - Prob. 25ECh. 17.4 - Giovanni Food Products produces and sells frozen...Ch. 17.4 - The number of users of Facebook from 2004 through...Ch. 17.5 - Consider the following time series.
Construct a...Ch. 17.5 - Consider the following time series...Ch. 17.5 - The quarterly sales data (number of copies sold)...Ch. 17.5 - Air pollution control specialists in southern...Ch. 17.5 - South Shore Construction builds permanent docks...Ch. 17.5 - Prob. 33ECh. 17.5 - Prob. 34ECh. 17.6 - Consider the following time series...Ch. 17.6 - Refer to exercise 35.
Deseasonalize the time...Ch. 17.6 - The quarterly sales data (number of copies sold)...Ch. 17.6 - Three years of monthly lawn-maintenance expenses...Ch. 17.6 - Air pollution control specialists in southern...Ch. 17.6 - Electric power consumption is measured in...Ch. 17 - The weekly demand (in cases) for a particular...Ch. 17 - The following table reports the percentage of...Ch. 17 - United Dairies, Inc., supplies milk to several...Ch. 17 - Prob. 44SECh. 17 - The Garden Avenue Seven sells CDs of its musical...Ch. 17 - The Mayfair Department Store in Davenport, Iowa,...Ch. 17 - Prob. 47SECh. 17 - The Costello Music Company has been in business...Ch. 17 - Consider the Costello Music Company problem in...Ch. 17 - Prob. 50SECh. 17 - Refer to the Costello Music Company time series in...Ch. 17 - Prob. 52SECh. 17 - Refer to the Hudson Marine problem in exercise 52....Ch. 17 - Refer to the Hudson Marine problem in exercise...Ch. 17 - Refer to the Hudson Marine data in exercise...Ch. 17 - Forecasting Food and Beverage Sales
The Vintage...Ch. 17 - The Carlson Department Store suffered heavy damage...
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