Essentials of Business Analytics (MindTap Course List)
Essentials of Business Analytics (MindTap Course List)
2nd Edition
ISBN: 9781305627734
Author: Jeffrey D. Camm, James J. Cochran, Michael J. Fry, Jeffrey W. Ohlmann, David R. Anderson
Publisher: Cengage Learning
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Chapter 8, Problem 24P

The quarterly sales data (number of copies sold) for a college textbook over the past three years are as follows:

Chapter 8, Problem 24P, The quarterly sales data (number of copies sold) for a college textbook over the past three years

  1. a. Construct a time series plot. What type of pattern exists in the data?
  2. b. Use a regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data: Qtr1 = l if quarter l, 0 otherwise; Qtr2 = l if quarter 2, 0 otherwise; Qtr3 = 1 if quarter 3, 0 otherwise.
  3. c. Based on the model you developed in part (b), compute the quarterly forecasts for next year.
  4. 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 equation to account for seasonal effects and any linear trend in the time series.
  5. e. Based upon the seasonal effects in the data and linear trend, compute the quarterly forecasts for next year.
  6. f. Is the model you developed in part (b) or the model you developed in part (d) more effective? Justify your answer.
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am. 13.
Table 13 lists fall graduate enrollment by gender in U.S. degree-granting institutions. The figure contains a scatter plot and regression line for each data set, where x represents years since 1980 and y represents enrollment in millions. Fall Graduate Enrollment (in millions) Year Male Female 1980 0.87 0.75 1990 0.90 0.96 2000 0.94 1.21 2010 1.21 1.73 2020 1.21 1.70     A. Interpret the slope of each model. B. Use the regression models to predict the male and female graduate enrollments in 2025. C. Use the regression models to estimate the first year in which female graduate enrollment will exceed male graduate enrollment by at least 1 million.
Consider the data in the Excel file Nuclear Power. Use simple linear regression to forecast the data. What would be the forecasts for the next three years? Nuclear Electric Power Production (Billion KWH)         Year US Canada France 1980 251.12 35.88 63.42 1981 272.67 37.8 99.24 1982 282.77 36.17 102.6 1983 293.68 46.22 136 1984 327.63 49.26 180.5 1985 383.69 57.1 211.2 1986 414.04 67.23 239.6 1987 455.27 72.89 249.3 1988 526.97 78.18 260.3 1989 529.35 75.35 288.7 1990 576.86 69.24 298.4 1991 612.57 80.68 314.8 1992 618.78 76.55 321.5 1993 610.29 90.08 349.8 1994 640.44 102.4 342 1995 673.4 92.95 358.4 1996 674.73 88.13 377.5 1997 628.64 77.86 375.7 1998 673.7 67.74 368.6 1999 728.25 69.82 374.5 2000 753.89 69.16 394.4 2001 768.83 72.86 400 2002 780.06 71.75 414.9 2003 763.73 71.15 419 2004 788.53 85.87 425.8 2005 781.99 87.44 429 2006 787.22 93.07 427.7

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Essentials of Business Analytics (MindTap Course List)

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