Question

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Homework 14 i Saved 13ahomeom The homeownership rate in the U.S. was 62.4% in 2009- In order to determine if homeownership is linked with income, 2009 state- level data on the homeownership rate (Ownership in %) and median household income (income in $) were collected. A portion of the data is shown in the accompanying table 5 ownership Income 36,660 58,284 points State Alabama Alaska 67.9 63.2 Wyoming 69.1 49,150 eBook Click here for the Excel Data File a-1. Estimate the model Ownership-Po + β|Income + e. (Negative values should be indicated by a minus sign. Round your answers to 4 decimal places.) [If you are using R to obtain the output, then first enter the following command at the prompt options(scipen-10). This will ensure that the output is not in scientific notation.] References Income a-2. Interpret the model. O For a $1 , 000 increase in income-homeownership rate is predicted to decrease by 0.01%. O For a $1 , 000 increase in income , homeownership rate is predicted to decrease by 0.1%. For a $1. 000 increase in income , homeownership rate is predicted to decrease by 0.001%. O For a $1.000 increase in income , homeownership rate is predicted to decrease by 0.0001%. b. What is the standard error of the estimate? (Round your answer to 2 decimal places.) Standard error c. Interpret the coefficient of determination O 1.50% of the sample variation in y is explained by the estimated regression equation. O 1.50% of the sample variation in x is explained by the estimated regression equation. O 2.50% of the sample variation in x is explained by the estimated regression equation. O 0.50% of the sample variation in y is explained by the estimated regression equation. State Ownership Income Arizona District of Columbia 0 Massachusetts New Hampshire North Dakota Rhode Island South Carolina South Dakota Washington

Answer 1

Date: 29/04/2019 Answer a-1) The regression equation of ownership (y) on income (x) is, By using Excel software, find regression equation with help of following stejps 1) Import the data. 2) Select Data Analysis from Data menu. 3) Select Regression and click Ok. 4)Input Y Range and Input X range. 5) Cick Ok.

SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square-0.005099266 Standard Error Observations 0.122485587 0.015002719 5.368801709 51 Coefficients Standard Error t Stat P-value 68.57006528 4.773092845 14.36596 3.41E-19 -8.75002E-05 Intercept Income 0.000101285 0.8639 0.39185 From the Excel output, the regression equation of ownership (y) on income (x) is, = 68.5701-0.0001x a-2)

Interpretationofslop =-0.0001 . For each unit increase in income, the mean ownership is estimated to decreases 0.0001. The answer is . b) The standard error ofestimate is, From Excel output in part (a-1), the standard error ofestimate is 5.37 c) Interpretation of coefficient of determination R2-0.0150 . 1.50% of sample variation in ownership 0) can be explained by the model containing income The answer is 1