To answer the questions that follow, download an Excel 8 spreadsheet containing the demographic data for a sample of 30 adults by clicking on the following words in bold: Download Excel File. Use Excel to obtain an estimated regression equation predicting the value of income from age. When you do this, also obtain a residual plot against age. (Note: Use the income [in $1,000 s] and age [years] variables, not the income or age category variables.) Which of the following is the best representation of your residual plot against age? Which of the following best describes the interpretation of the shape of the residual plot against age? The residual plot suggests that the variance of the error is constant for all values of x (age). This suggests that the assumed regression model adequately represents the relationship between income and age. The residual plot suggests that the variance of the error decreases for larger values of x (age). This suggests that the assumption of constant variance may be violated. The residual plot suggests that the assumed regression model does not adequately represent the relationship between income and age. A curvilinear relationchip should be considered; Also, obtain a residual plot against . How does the shape of the plot you obtain differ from your residual plot against age? The shape of two plots are very similar. The shape of the residual plot against is very similar to the mirror image of the shape of the residual plot against x. The shape of the two plots are very different. To answer the questions that follow, download an Excel 8 spreadsheet containing the demographic data for a sample of 30 adults by clicking on the following words in bold: Download Excel File. Use Excel to obtain an estimated regression equation predicting the value of income from age. When you do this, also obtain a residual plot against age. (Note: Use the income [in $1,000 s] and age [years] variables, not the income or age category variables.) Which of the following is the best representation of your residual plot against age? Which of the following best describes the interpretation of the shape of the residual plot against age? The residual plot suggests that the variance of the error is constant for all values of x (age). This suggests that the assumed regression model adequately represents the relationship between income and age. The residual plot suggests that the variance of the error decreases for larger values of x (age). This suggests that the assumption of constant variance may be violated. The residual plot suggests that the assumed regression model does not adequately represent the relationship between income and age. A curvilinear relationchip should be considered; Also, obtain a residual plot against . How does the shape of the plot you obtain differ from your residual plot against age? The shape of two plots are very similar. The shape of the residual plot against is very similar to the mirror image of the shape of the residual plot against x. The shape of the two plots are very different