Essentials Of Business Analytics
Essentials Of Business Analytics
1st Edition
ISBN: 9781285187273
Author: Camm, Jeff.
Publisher: Cengage Learning,
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Chapter 5, Problem 26P

South Shore Construction builds permanent docks and seawalls along the southern shore of Long Island, New York. Although the firm has been in business only five years, revenue has increased from $308,000 in the first year of operation to $1,084,000 in the most recent year. The following data show the quarterly sales revenue in thousands of dollars:

Chapter 5, Problem 26P, South Shore Construction builds permanent docks and seawalls along the southern shore of Long

  1. a. Construct a time series plot. What type of pattern exists in the data?
  2. b. 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 I, 0 otherwise; Qtr2 = 1 if quarter 2, 0 otherwise; Qtr3 = 1 if quarter 3, 0 otherwise.
  3. c. Based on the model you developed in part (b), compute estimates of quarterly sales for year 6.
  4. d. Let Period = 1 refer to the observation in quarter 1 of year 1; Period = 2 refer to the observation in quarter 2 of year 1; … and Period = 20 refer to the observation in quarter 4 of year 5. Using the dummy variables defined in part (b) and the variable Period, develop an equation to account for seasonal effects and any linear trend in the time series.
  5. e. Based on the seasonal effects in the data and linear trend estimated in part (c), compute estimates of quarterly sales for year 6.
  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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Year No. of Eastern Bluebird 1970 200 1975 300 1980 125 1985 250 1990 425 1995 450 2000 575 2005 675 2010 500 a) Make a scatter plot of the number of birds vs. year record. b) Create a table with this data that compares Years Since 1900 vs. the number of birds. Fill in extra columns for Years-Since-Squared and Years*Birds. Complete the table by adding rows for column totals and column averages. c) Calculate the linear regression for this model. e) Calculate the correlation coefficient for this model. f) Translate your linear regression so that the model is now Year vs. Number of birds. g) Add the model to your scatter plot. h) Compute the residual errors for your model. i) Plot your residual errors. j) Interpolate your model to find the number of birds in 1983 and 2001.
Suppose a firm has had the following historic sales figures. Year: 2016 2017 2018 2019 2020 Sales $2,430,000 $3,650,000 $4,300,000 $5,010,000 $5,660,000 What would be the forecast for next year's sales using regression to estimate a trend? Next year's sales
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