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
expand_more
expand_more
format_list_bulleted
Textbook Question
Chapter 17.6, Problem 36E
Refer to exercise 35.
- a. Deseasonalize the time series using the adjusted seasonal indexes computed in part (c) of exercise 35.
- b. Compute the linear trend regression equation for the deseasonalized data.
- c. Compute the deseasonalized quarterly trend forecast for Year 4.
- d. Use the seasonal indexes to adjust the deseasonalized trend forecasts computed in part (c).
35. Consider the following time series data.
- a. Construct a time series plot. What type of pattern exists in the data?
- b. Show the four-quarter and centered moving average values for this time series.
- c. Compute seasonal indexes and adjusted seasonal indexes for the four quarters.
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solutionStudents have asked these similar questions
Compute the forecasted values for Yt for July and August in 2020 by using the modelsstated in (c) and (d)
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
Consider the following time series.t 1 2 3 4 5 6 7 Yt 120 110 100 96 94 92 88a. What type of pattern exists in the data?HorizontalSeasonal with upward trendDownward trendUpward trendSeasonal with downward trendb. Regression analysis yields the following forecast equation: 119.71 - 4.929t; what is the forecast for period 8? Round to the nearest hundredth.c. Regression analysis yields the following forecast equation: 119.71 - 4.929t; what is the MSE for this forecast method? Round to the nearest hundredth.
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.
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 - Annual retail store revenue for Apple from 2007 to...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...
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.Similar questions
- Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?arrow_forwardBelow you are given the first five values of a quarterly time series. The multiplicative model is appropriate and a four-quarter moving average will be used. Year Quarter Time Series Value Yt 1 1 36 2 24 3 16 2 4 20 1 44 An estimate of the combined trend-cycle component (T2Ct) for Quarter 3 of Year 1 (used for estimating the de-trended values), when a four-quarter moving average is used, is a. 24. b. 26. c. 28. d. 25.arrow_forwardWhich of the following time series forecasting methods would not be used to forecast seasonal data?arrow_forward
- The president of small manufacturing firm is concerned about the continual increase in manufacturing costs over the past several years. The following figures provide a time series of the cost per unit for the firm’s leading product over the past eight years. Year Cost/Unit ($) Year Cost/Unit ($) 1 20.00 5 26.60 2 24.50 6 30.00 3 28.20 7 31.00 4 27.50 8 36.00 Construct a time series plot. What type of pattern exists in the data? Use simple linear regression analysis to find the parameters for the line that minimizes MSE for this time series. What is the average cost increase that the firm has been realizing per year? Compute an estimate of the cost/unit for next year.arrow_forwardConsider 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…arrow_forwardConsider 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 4arrow_forward
- 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 A. Use a multiple regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data: Q1 if quarter 1, 0 otherwise; Q2 if quarter 2, 0 otherwise; Q3 if quarter 3, 0 otherwise. B. Use a multiple regression model to develop an equation to account for trend and seasonal effects in the data. Use the dummy variables you developed in part (A) to capture seasonal effects and create a variable "Trend" such that T=1 for quarter 1 in year 1, T=2 for quarter 2 in year1,.... T=12 for quarter 4 in year 3.arrow_forwardCinema HD an online movie streaming service that offers a wide variety of award-winning TV shows, movies, animes, and documentaries, would like to determine the mathematical trend of memberships in order to project future needs. Year 2013 2014 2015 2016 2017 2018 2019 2020 2021 Membership 17 16 16 21 20 20 23 25 24 Use the following time series data, to develop a regression equation relating memberships to time. Forecast 2023 membership Assuming the COVID-19 pandemic comes to an end in 2021, in your opinion, how will this affect membership? Why? How will this affect your prediction? What are the issues associated with qualitative forecasting, and how are these overcome? Provide an example of qualitative forecasting and explain the shortcomings.arrow_forwardConsider the following time series data Week 1 2 3 4 5 6 Value 18 13 16 11 17 14 a. Construct a time series plot. What type of pattern exists in the data?b. Develop the three-week moving average forecasts for this time series. compute MSE and a forecast for week 7.c. Use α = .2 to compute the exponential smoothing forecasts for the time series.Compute MSE and a forecast for week 7.d. Compare the three-week moving average approach with the exponentialsmoothing approach using α = .2. Which appears to provide more accurate forecasts based on MSE? explain.e. Use a smoothing constant of α = .4 to compute the exponential smoothing forecasts. does a smoothing constant of .2 or .4 appear to provide more accurate forecasts based on MSE? explain.arrow_forward
- After its move in 1990 to La Junta, Colorado, and its new initiatives, the DeBourgh Manufacturing Company began an upward climb of record sales. Suppose the figures shown here are the DeBourgh monthly sales figures from January 2001 through December 2009 (in $1,000s). a) Produce a time series plot. Are there any trends evident in the data? Does DeBourgh have a seasonal component to its sales? b) Deseasonalize the data using Multiplicative model with a 0.5 weighted moving average. Produce a time series plot of the deseasonalized data and add a trendline. c) Forecast the sales from January to December of the year 2010. d) Include a discussion of the general direction of sales and any seasonal tendencies that might be occurrinG Month 2001 2002 2003 2004 2005 2006 2007 2008 2009 January 139.7 165.1 177.8 228.6 266.7 431.8 381 431.8 495.3 February 114.3 177.8 203.2 254 317.5 457.2 406.4 444.5 533.4 March 101.6 177.8 228.6 266.7 368.3 457.2 431.8 495.3 635 April 152.4 203.2…arrow_forwardEditor of Astrology Magazine wants to obtain sales forecast value for 2021. Use the given data below and help the editor. Year Quarter Sales 2019 1. 53 2. 51 3. 48 4. 55 2020 1. 53 2. 51 3. 54 4. 52 Use time series regression model and determine sales forecast value for the second quarter of 2021arrow_forwardMovieflix, an online movie streaming service that offers a wide variety of award-winning TV shows, movies, animes, and documentaries, would like to determine the mathematical trend of memberships in order to project future needs.Year 2013 2014 2015 2016 2017 2018 2019 2020 2021Membership (000s)17 16 16 21 20 20 23 25 24 (i) Use the following time series data, to develop a regression equation relating memberships to time.arrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
- College AlgebraAlgebraISBN:9781305115545Author:James Stewart, Lothar Redlin, Saleem WatsonPublisher:Cengage Learning
College Algebra
Algebra
ISBN:9781305115545
Author:James Stewart, Lothar Redlin, Saleem Watson
Publisher:Cengage Learning
Time Series Analysis Theory & Uni-variate Forecasting Techniques; Author: Analytics University;https://www.youtube.com/watch?v=_X5q9FYLGxM;License: Standard YouTube License, CC-BY
Operations management 101: Time-series, forecasting introduction; Author: Brandoz Foltz;https://www.youtube.com/watch?v=EaqZP36ool8;License: Standard YouTube License, CC-BY