Use the “CO2Concentration” dataset, which contains the average carbon dioxide concentration (labeled CO2) for 161 months. The two columns labeled CO2lag1 and CO2lag2 contain lag 1 carbon dioxide concentration and lag 2 carbon dioxide concentration. Lag 1 corresponds to values from the previous month and lag 2 corresponds to values from two months ago. (a) Determine partial autocorrelations for the carbon dioxide concentration series. What do the results indicate about an auto-regression model for a time series that describes carbon dioxide concentration? That is, what are the “large” partial autocorrelations? (b) Do a multiple regression with CO2 as the y-variable and CO2lag1 and CO2lag2 values as x-variables. Store the residuals. i. Write the estimated regression equation. ii. Use the regression equation to find the fitted value for the carbon dioxide concentration for the 162nd month. [For this question you don’t need to use the method at the bottom
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