Modern Business Statistics with Microsoft Office Excel (with XLSTAT Education Edition Printed Access Card) (MindTap Course List)
6th Edition
ISBN: 9781337115186
Author: David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J. Cochran
Publisher: Cengage Learning
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Textbook Question
Chapter 17.6, Problem 39E
Air pollution control specialists in southern California monitor the amount of ozone, carbon dioxide, and nitrogen dioxide in the air on an hourly basis. The hourly time series data exhibit seasonality, with the levels of pollutants showing patterns over the hours in the day. On July 15, 16, and 17, the following levels of nitrogen dioxide were observed in the downtown area for the 12 hours from 6:00 A.M. to 6:00 P.M.
- a. Construct a time series plot. What type of pattern exists in the data?
- b. Identify the hourly seasonal indexes for the 12 readings each day.
- c. Deseasonalize the time series.
- d. Compute the linear trend equation for the deseasonalized data.
- e. Compute the deseasonalized trend forecasts for the 12 hours for July 18 and then adjust the trend forecasts using the seasonal indexes computed in part (b).
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Chapter 17 Solutions
Modern Business Statistics with Microsoft Office Excel (with XLSTAT Education Edition Printed Access Card) (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 $...Ch. 17.3 - The following time series shows the sales of a...Ch. 17.3 - Ten weeks of data on the Commodity Futures Index...Ch. 17.3 - Prob. 16ECh. 17.4 - Consider the following time series...Ch. 17.4 - Prob. 18ECh. 17.4 - Prob. 19ECh. 17.4 - Prob. 20ECh. 17.4 - Prob. 21ECh. 17.4 - Prob. 22ECh. 17.4 - The president of a small manufacturing firm is...Ch. 17.4 - The following data shows the average interest rate...Ch. 17.4 - Quarterly revenue ($ millions) for Twitter for the...Ch. 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.
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