Question 6The variable yearly income is examined in a regression setting where the predictor variableis lag (1) of income and the following output is produced.us_change %>%model (TSLM (log (Income) ~ log (LagIncome))) %>%report ()#> Series: Consumption#> Model: TSLM#>#> Residuals:Min10 Median30#> -2.5824 -0.2778 0.0186 0.3233#>#> Coefficients:Max1.4223#>#> (Intercept) 0.5445#> Log (LagIncome) 0.1000#>Estimate Std. Error t value Pr (>|t|)0.0540 10.08 < 2e-16 ***0.0467 0.582 0.242#> Signif. codes: 0 ***** 0.001 **** 0.01 * 0.05. 0.1#>#> Residual standard error: 0.591 on 196 degrees of freedom#> Multiple R-squared: 0.0847, Adjusted R-squared: 0.08431a) Write down the regression equation.b) Interpret the meaning of the slope.c) Explain whether this model is appropriate to use for forecasting based on this output.d) A dummy variable for gender (male=0, female=1) was added to the model. Interpretits coefficient of 0.1..

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Trigonometry (MindTap Course List)

8th Edition

ISBN:9781305652224

Author:Charles P. McKeague, Mark D. Turner

Publisher:Charles P. McKeague, Mark D. Turner

Chapter4: Graphing And Inverse Functions

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Problem 6GP: If your graphing calculator is capable of computing a least-squares sinusoidal regression model, use...

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