Essentials Of Business Analytics
1st Edition
ISBN: 9781285187273
Author: Camm, Jeff.
Publisher: Cengage Learning,
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Textbook Question
Chapter 5, Problem 23P
Consider the following time series data:
- a. Construct a time series plot. What type of pattern exists in the data?
- 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 1, 0 otherwise; Qtr2 = 1 if quarter 2. 0 otherwise; Qtr3 = 1 if quarter 3, 0 otherwise.
- c. Compute the quarterly forecasts for next year based on the model you developed in part (b).
- d. 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 (b) to capture seasonal effects and create a variable t such that t = 1 for quarter 1 in year 1, t = 2 for quarter 2 in year 1, … t = 12 for quarter 4 in year 3.
- e. Compute the quarterly forecasts for next year based on the model you developed in part (d).
- 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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The details of the clock sales at a supermarket for the past 6 weeks are shown in the table below. The time series appears to be relatively stable, without trend, seasonal, or cyclical effects. The simple moving average value of k is set at 2. If the smoothing constant is assumed to be 0.7, and setting
F1 and F2=A1,
what is the exponential smoothing sales forecast for week 7? Round to the nearest whole number.
Week
Units sold
1
88
2
44
3
54
4
65
5
72
6
85
Question content area bottom
Part 1
A.
80 clocks
B.
60 clocks
C.
70 clocks
D.
50 clocks
The details of the clock sales at a supermarket for the past 6 weeks are shown in the table below. The time series appears to be relatively stable, without trend, seasonal, or cyclical effects. The simple moving average value of k is set at 2. Calculate the value of the simple moving average mean absolute percentage error. Round to two decimal places.
Week
Units sold
1
88
2
44
3
54
4
65
5
72
6
85
Part 1
A.
14.39
B.
25.56
C.
23.45
D.
20.90
The accompanying data shows the fossil fuels production, fossil fuels consumption, and total energy consumption in quadrillions of BTUs of a certain region for the years 1986 to 2015. Complete parts a and b.
Year Fossil Fuels Production Fossil Fuels Consumption Total Energy Consumption1949 28.748 29.002 31.9821950 32.563 31.632 34.6161951 35.792 34.008 36.9741952 34.977 33.800 36.7481953 35.349 34.826 37.6641954 33.764 33.877 36.6391955 37.364 37.410 40.2081956 39.771 38.888 41.7541957 40.133 38.926 41.7871958 37.216 38.717 41.6451959 39.045 40.550 43.4661960 39.869 42.137 45.0861961 40.307 42.758 45.7381962 41.732 44.681 47.8261963 44.037 46.509 49.6441964 45.789 48.543 51.8151965 47.235 50.577 54.0151966 50.035 53.514 57.0141967 52.597 55.127 58.9051968 54.306 58.502 62.4151969 56.286…
Chapter 5 Solutions
Essentials Of Business Analytics
Ch. 5 - Consider the following time series data:
Using...Ch. 5 - Refer to the time series data in Problem 1. Using...Ch. 5 - Problems 1 and 2 used different forecasting...Ch. 5 - Consider the following time series data:
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Ch. 5 - Corporate triple A bond interest rates for 12...Ch. 5 - The values of Alabama building contracts (in...Ch. 5 - The following time series shows the sales of a...Ch. 5 - Prob. 15PCh. 5 - The following table reports the percentage of...Ch. 5 - Consider the following time series: a. Construct a...Ch. 5 - Consider the following time series:
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