Nela’ Statistics Homework “Multiple Regression” Ex: XXXXXXXXXX, and 17.46 “Time Series Analysis and Forecasting” Ex: 20.19 and 20.35 Submit your answers in a Microsoft Excel Workbook, with each...

Nela’ Statistics Homework
“Multiple Regression” Ex: 17.39 17.42, and 17.46
“Time Series Analysis and Forecasting” Ex: 20.19 and 20.35
Submit your answers in a Microsoft Excel Workbook, with each problem on a separate worksheet; Label each tab in the workbook with the exercise number. Highlight the answers in yellow and provide an interpretation in a text book.
Exercise 17.29
Perform the Durbin-Watson test at the 5% significance level to determine whether positive first-order autocorrelation exists when d=1.10, n=25, and k=3.
Exercise 17.32
Test the following hypothesis with alpha = .05
Ho: There is no first-order autocorrelation
H1: There is positive first-order outocorrelation
n = 50, k=2, d=1.38
Exercise 17.36
Weekly sales of a company’s product (y) and those in its main competitor (x) were recorded for one year.

  1. Conduct a regression analysis of these data.

  2. Plot the residuals versus the time periods. Does there appear to be autocorrelation?

  3. Perform the Durbin-Watson test. Is there evidence of autocorrelation? Use alpha=.10.

  4. If autocorrelation was detected in Part c, propose an alternative regression model to remedy the problem. Use the computer to generate the statistics associated with this model.

  5. Redo Parts b and c. Compare the two methods.


Exercise 20.19
Plot the following time series to determine which of the trend models appears to fit better.
Period 1 2 3 4 5
Time series 55 57 53 49 47
Period 6 7 8 9 10
Time series 39 41 33 28 20
Exercise 20.35
The following trend line and seasonal indexes were computed from 4 weeks of daily observations. Forecast the seven values for next week.
Y=120 + 2.3t t= 1, 2,……, 28
Day Seasonal Index
Sunday 1.5
Monday .4
Tuesday .5
Wednesday .6
Thursday .7
Friday 1.4
Saturday 1.9



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Nela’ Statistics Homework “Multiple Regression” Ex: 17.39 17.42, and 17.46 “Time Series Analysis and Forecasting” Ex: 20.19 and 20.35 Submit your answers in a Microsoft Excel Workbook, with each problem on a separate worksheet; Label each tab in the workbook with the exercise number. Highlight the answers in yellow and provide an interpretation in a text book. Exercise 17.29 Perform the Durbin-Watson test at the 5% significance level to determine whether positive first-order autocorrelation exists when d=1.10, n=25, and k=3. Exercise 17.32 Test the following hypothesis with alpha = .05 Ho: There is no first-order autocorrelation H1: There is positive first-order outocorrelation n = 50, k=2, d=1.38 Exercise 17.36 Weekly sales of a company’s product (y) and those in its main competitor (x) were recorded for one year. Conduct a regression analysis of these data. Plot the residuals versus the time periods. Does there appear to be autocorrelation? Perform the Durbin-Watson test. Is there evidence of autocorrelation? Use alpha=.10. If autocorrelation was detected in Part c, propose an alternative regression model to remedy the problem. Use the computer to generate the statistics associated with this model. Redo Parts b and c. Compare the two methods. Exercise 20.19 Plot the following time series to determine which of the trend models appears to fit better. Period 1 2 3 4 5 Time series 55 57 53 49 47 Period 6 7 8 9 10 Time series 39 41 33 28 20 Exercise 20.35 The following trend line and seasonal indexes were computed from 4 weeks of daily observations. Forecast the seven values for next week. Y=120 + 2.3t t= 1, 2,……, 28 Day Seasonal Index Sunday 1.5 Monday .4 Tuesday ...



May 14, 2022
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