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Scenario: An appliance manufacturer is doing a regression analysis, using quarterly time-series data, of the factors affecting its sales of appliances. A regression equation was estimated between appliance sales (in dollars) as the dependent variable and disposable personal income and new housing starts as the independent variables. The statistical tests of the model showed large t-values for both independent variables, along with a high r2 value. However, analysis of the residuals indicated that substantial autocorrelation was present. a. What are some of the possible causes of this autocorrelation? b. How does this autocorrelation affect the conclusions concerning the significance of the individual explanatory variables and the overall explanatory power of the regression model? c. Given that a person uses the model for forecasting future appliance sales, how does this autocorrelation affect the accuracy of these forecasts? d. What techniques might be used to remove this autocorrelation from the model?
the problem of public-sector employee performanceit is generally recognized that one of the core problems of
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You should comment on the success and/or failure of its approach and implementation as stated in the text and posted readings and how it may have modified its organization, supply or marketing over time given changes in its markets
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