DATA EXCEl:

Ownership Income State Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware District of Columbia Florida Georgia Hawaii Idaho Illinois Indiana lowa Kansas Kentucky 66.135670 62.157294 62.441429 60.4 32228 52.6 51824 63.151620 65.8 70.2 478044 41.348831 64.2 41321 60.739030 54.9 51339 68.5 42468 63.5 65.039995 66.2 46411 60.9 40407 64.0 38354 65.141123 67.343192 64.959876 60.4 55063 67.5 67.3 51780 66.2 30768 65.644459 63.2 36127 64.1 45285 57.247124 70.9 61.5 60467 62.339232 49.745906 62.937596 60.045765 63.2 41569 4 6 8 60541 10 13 15 16 48560 18 19 0Louisiana Maine Maryland Massachusetts Michigan Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York North Carolina North Dakota Ohio 23 24 25 26 27 28 29 30 41684 59821 32 34 35 37 Oklahoma Oregon Pennsylvania Rhode Island South Carolina South Dakota Tennessee Texas Utah Vermont Virginia Washington West Virginia Wisconsin Wyoming 63.1 41568 62.2 44788 65.743862 57.647324 66.636791 63.1 41516 63.5 36207 59.5 43165 68.654181 68.2 64.756191 60.856082 70.3 64.546927 67.7 48008 36180 48160 Check my work The homeownership rate in the U.S. was 60.9% 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. State Alabama Alaska Ownership Income 35,670 57,294 66.1 62.1 Wyoming 67.7 48,160 Click here for the Excel Data File Click here for the CSV Data File a-1. Estimate the model Ownership = 0 + Aincome + 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.] Income a-2. Interpret the model. O For a $1000 increase in income, homeownership rate is predicted to decrease by 0.01%. O For a $1000 increase in income, homeownership rate is predicted to decrease by 0.2%. For a $1000 increase in income, homeownership rate is predicted to decrease by 0.002%. For a $1000 increase in income, homeownership rate is predicted to decrease by 0.002%. b. What is the standard error of the estimate? (Round your answer to 2 decimal places.) Standard error c. Interpret the coefficient of determination / 0.66% of the sample variation in y is explained by the estimated regression equation. 0 618% of the sample variation in x is explained by the estimated regression equation. 04.27% of the sample variation in x is explained by the estimated regression equation. 02.48% of the sample variation in y is explained by the estimated regression equation Ownership Income State Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware District of Columbia Florida Georgia Hawaii Idaho Illinois Indiana lowa Kansas Kentucky 66.135670 62.157294 62.441429 60.4 32228 52.6 51824 63.151620 65.8 70.2 478044 41.348831 64.2 41321 60.739030 54.9 51339 68.5 42468 63.5 65.039995 66.2 46411 60.9 40407 64.0 38354 65.141123 67.343192 64.959876 60.4 55063 67.5 67.3 51780 66.2 30768 65.644459 63.2 36127 64.1 45285 57.247124 70.9 61.5 60467 62.339232 49.745906 62.937596 60.045765 63.2 41569 4 6 8 60541 10 13 15 16 48560 18 19 0Louisiana Maine Maryland Massachusetts Michigan Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York North Carolina North Dakota Ohio 23 24 25 26 27 28 29 30 41684 59821 32 34 35 37 Oklahoma Oregon Pennsylvania Rhode Island South Carolina South Dakota Tennessee Texas Utah Vermont Virginia Washington West Virginia Wisconsin Wyoming 63.1 41568 62.2 44788 65.743862 57.647324 66.636791 63.1 41516 63.5 36207 59.5 43165 68.654181 68.2 64.756191 60.856082 70.3 64.546927 67.7 48008 36180 48160 Check my work The homeownership rate in the U.S. was 60.9% 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. State Alabama Alaska Ownership Income 35,670 57,294 66.1 62.1 Wyoming 67.7 48,160 Click here for the Excel Data File Click here for the CSV Data File a-1. Estimate the model Ownership = 0 + Aincome + 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.] Income a-2. Interpret the model. O For a $1000 increase in income, homeownership rate is predicted to decrease by 0.01%. O For a $1000 increase in income, homeownership rate is predicted to decrease by 0.2%. For a $1000 increase in income, homeownership rate is predicted to decrease by 0.002%. For a $1000 increase in income, homeownership rate is predicted to decrease by 0.002%. b. What is the standard error of the estimate? (Round your answer to 2 decimal places.) Standard error c. Interpret the coefficient of determination / 0.66% of the sample variation in y is explained by the estimated regression equation. 0 618% of the sample variation in x is explained by the estimated regression equation. 04.27% of the sample variation in x is explained by the estimated regression equation. 02.48% of the sample variation in y is explained by the estimated regression equation