Time Series Analysis and Regression & Seasonal Index
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Determining a Seasonal Index
Listed below is the net sales in $ million for Home Depot, Inc. and its subsidiaries from 1993 to 2002.
Year Net Sales
1993 9,239
1994 12,477
1995 15,470
1996 19,535
1997 24,156
1998 30,219
1999 38,434
2000 45,738
2001 53,553
2002 58,247
Determine the least squares equation. On the basis of this information, what are the estimated sales for 2005?
The Appliance Center sells a variety of electronic equipment and home appliances. For the last four years the following quarterly sales (in $ millions) were reported.
Quarter
Year I II III IV
2000 5.3 4.1 6.8 6.7
2001 4.8 3.8 5.6 6.8
2002 4.3 3.8 5.7 6.0
2003 5.6 4.6 6.4 5.9
Determine a typical seasonal index for each of the four quarters.
REGRESSION ANALYSIS
14. Mr. James McWhinney, president of Daniel-James Financial Services, believes there is a relationship between the number of client contacts and the dollar amount of sales. To document this assertion, Mr. McWhinney gathered the following sample information. The X column indicates the number of client contacts last month, and the Y column shows the value of sales ($ thousands) last month for each client sampled.
Number of Contacts, X Sales ($ thousands), Y Number of Contacts, X Sales ($ thousands), Y
14 24 23 30
12 14 48 90
20 28 50 85
16 30 55 120
46 80 50 110
Determine the regression equation.
Determine the estimated sales if 40 contacts are made.
Refer to Exercise above.
a. Determine the standard error of estimate.
b. Suppose a large sample is selected (instead of just 10). About 95 percent of the predictions regarding sales would occur between what two values?
Please use Excel show formula used
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Solution Summary
Step by step method for regression analysis is discussed here. Regression coefficients, coefficient of determination, scatter diagram and significance of regression model are explained in the solution.
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