Statistics for Business & Economics, Revised (MindTap Course List)
12th Edition
ISBN: 9781285846323
Author: David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J. Cochran
Publisher: South-Western College Pub
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. Using Minitab or Excel, 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
Trending nowThis is a popular solution!
Students 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
Cinema 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.
Chapter 17 Solutions
Statistics for Business & Economics, Revised (MindTap Course List)
Ch. 17.2 - Consider the following time series data. Week 1 2...Ch. 17.2 - Refer to the time series data in exercise 1. Using...Ch. 17.2 - Exercises 1 and 2 used different forecasting...Ch. 17.2 - Consider the following time series data. Month 1 2...Ch. 17.3 - Consider the following time series data. Week 1 2...Ch. 17.3 - Consider the following time series data. Month 1 2...Ch. 17.3 - Refer to the gasoline sales time series data in...Ch. 17.3 - Refer again to the gasoline sales time series data...Ch. 17.3 - With the gasoline time series data from Table...Ch. 17.3 - With a smoothing constant of = .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 - The U.S. Census Bureau tracks the median price for...Ch. 17.4 - Consider the following time series data. a....Ch. 17.4 - Prob. 18ECh. 17.4 - Consider the following time series. a. Construct a...Ch. 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 - Automobile unit sales at B. J. Scott Motors, Inc.,...Ch. 17.4 - Giovanni Food Products produces and sells frozen...Ch. 17.4 - Prob. 27ECh. 17.5 - Consider the following time series. a. Construct a...Ch. 17.5 - Consider the following time series data. a....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 - Three years of monthly lawn-maintenance expenses...Ch. 17.6 - Consider the following time series data. a....Ch. 17.6 - Refer to exercise 35. a. 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 - Prob. 45SECh. 17 - The Mayfair Department Store in Davenport, Iowa,...Ch. 17 - Canton Supplies, Inc., is a service firm that...Ch. 17 - The Costello Music Company has been in business...Ch. 17 - Consider the Costello Music Company problem in...Ch. 17 - Refer to the Costello Music Company problem in...Ch. 17 - Refer to the Costello Music Company time series in...Ch. 17 - Hudson Marine has been an authorized dealer for CD...Ch. 17 - Refer to the Hudson Marine problem in exercise 52....Ch. 17 - Refer to the Hudson Marine problem in exercise 53....Ch. 17 - Refer to the Hudson Marine data in exercise 53. a....Ch. 17 - Forecasting Food and Beverage Sales The Vintage...Ch. 17 - Forecasting Lost Sales The Carlson Department...
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_forwardConsider 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.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_forward
- The sales records of a major auto manufacturer over the past years from 2005 to 2019 are shown below. Number of Cars Sold Year (In thousands of Units) 2005 195 2006 200 2007 250 2008 270 2009 320 2010 380 2011 440 2012 460 2013 500 2014 500 2015 550 2016 570 2017 600 2018 650 2019 700 Develop moving average with k=4 and compute its MSE Develop exponential model with α = 0.4 and compute its MSE Develop a linear trend model and compute its MSE Based on the MSE computed fore ach model , which model fits well to the data Based on the answer of question (4) forecast the number of cars sold for year 2020.arrow_forwardA pharmacist has been monitoring sales of a certain over-the-counter pain reliever. Daily sales duringthe last 15 days wereDay: 1 2 3 4 5 6 7 8 9Number sold: 36 38 42 44 48 49 50 49 52Day: 10 11 12 13 14 15Number sold: 48 52 55 54 56 57a. Which method would you suggest using to predict future sales—a linear trend equation or trendadjustedexponential smoothing? Why?b. If you learn that on some days the store ran out of the specific pain reliever, would that knowledgecause you any concern? Explain.c. Assume that the data refer to demand rather than sales. Using trend-adjusted smoothing with aninitial forecast of 50 for week 8, an initial trend estimate of 2, and .3, develop forecastsfor days 9 through 16. What is the MSE for the eight forecasts for which there are actual data?arrow_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
- hudson Marine has been an authorized dealer for c&d marine radios for the past sevenyears. the following table reports the number of radios sold each year.Year 1 2 3 4 5 6 7Number Sold 35 50 75 90 105 110 130a. construct a time series plot. does a linear trend appear to be present?b. Using Minitab or excel, develop a linear trend equation for this time series.c. Use the linear trend equation developed in part (b) to develop a forecast for annualsales in year 8.arrow_forwardA pharmacist has been monitoring sales of a certain over-the-counter pain reliever. Daily sales during the last 15 days were Day: 1 2 3 4 5 6 7 8 9 Number sold: 34 37 40 39 45 43 47 49 48 Day: 10 11 12 13 14 15 Number sold: 52 53 47 53 47 49 a. Assume the data refer to demand rather than sales. Using trend-adjusted exponential smoothing with an initial forecast of 42 for Day 8, an initial trend estimate of 2, and α = β = .3, develop demand forecasts for Days 9 through 16. Then compute the resultant MSE using the error values from Days 8 through 15. (Round your intermediate period-by-period forecast and error values to 3 decimal places. Round your final MSE answer to 3 decimal places.) MSEarrow_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 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?arrow_forward
- Editor 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_forwardDoes the sugar cane model suffer from heteroscedasticity? Perform a Breusch-Pegan test as well as a Whitetest to verify what the residual plots suggests, based on the following regression results:arrow_forward4) the accompanying dataset provides data on monthly unemployment rates for a certain region over four years. Compare 3- and 12- month moving average forecast using the MAD criterion. Which of the two models yields better results? (See picture) Find the MAD for the 3 month moving average forcast. MAD = _____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