Answer Happy

A regional planner employed by a public university is studying the demographics of nine counties in the eastern region of an Atlantic seaboard state. She has gathered the following data: County Median Income Median Age Coastal A $48,952 48.3 B 46,669 58.8 с 47,780 48.0 0 D 46,855 39.2 1 E 37,724 51.9 1 F 35,414 56.2 1 G 34,389 49.1 0 H 38,128 30.3 0 I 30,384 38.9 Click here for the Excel Data File a. Is there a linear relationship between the median income and median age? (Round your answer to 3 decimal places.) The correlation of Income and Median Age is
b. Which variable is the "dependent" variable? O Median Age O Median Income c-1. Use regression analysis to determine the relationship between median income and median age. (Round your answers to 2 decimal places.) Income = Median Age c-2. Interpret the value of the slope in a simple regression equation. (Round your answer to 2 decimal places.) For each year in age, the income increases on average.
d. Include the aspect that the county is "coastal" or not in a multiple linear regression analysis using a "dummy" variable. (Negative amounts should be indicated by a minus sign. Round your answers to 2 decimal places.) Income = Median Age + Coastal e. Test each of the individual coefficients to see if they are significant. (Negative amounts should be indicated by a minus sign. Leave no cells blank - be certain to enter "0" wherever required. Round your answers to 2 decimal places.) Predictor p-value Constant Median Age Coastal
Regression Assignment am of the residuals. Which plot is correct? Residual plot 1 Residual plot Normal 2.5- 2.0 2.0 1.5- 1.5 1.0- 0.5 0.0 -10000 -5000 0 5000 10000 15000 Residual O Plot 1 O Plot 2 O Plot 3 Make a scatter diagram of the residual values versus the fitted values Which plot is correct? Frequency 1.0 0.5 0.0 -15000 Mean -8.08440E-13 StDev 6267 N 9 Frequency -3000 -2000 -1000 Residual plot 2 Residual plot Normal 0 1000 Residual 2000 3000 Mean 4.85064E-1 StDev 156 N
g. Make a scatter diagram of the residual values versus the fitted values. Which plot is correct? Residuals vs Fits 1 Residuals vs Fits for LCD's 10000 1000 500 5000 0 0 -500 -5000 -1000- -1500 -10000 39000 40000 41000 FITS Residual O Plot 1 37000 38000 O Plot 2 O Plot 3 42000 43000 44000 Residual 35000 37500 Residuals vs Fits 2 Residuals vs Fits for LCD's 40000 42500 FITS 45000 47500 5000