Question

State	Ownership (%)	Income ($)
Alabama	66.7	36000
Alaska	62.5	57624
Arizona	62.9	41759
Arkansas	61.0	32558
California	53.0	52154
Colorado	63.5	51950
Connecticut	66.2	60871
Delaware	70.7	48134
District of Columbia	41.5	49161
Florida	64.7	41651
Georgia	61.2	39360
Hawaii	55.2	51669
Idaho	69.1	42798
Illinois	63.9	48890
Indiana	65.5	40325
Iowa	66.7	46741
Kansas	61.4	40737
Kentucky	64.6	38684
Louisiana	65.6	41453
Maine	67.8	43522
Maryland	65.3	60206
Massachusetts	60.7	55393
Michigan	68.1	42014
Minnesota	67.7	52110
Mississippi	66.9	31098
Missouri	66.1	44789
Montana	63.7	36457
Nebraska	64.6	45615
Nevada	57.6	47454
New Hampshire	71.3	60151
New Jersey	61.9	60797
New Mexico	62.8	39562
New York	50.1	46236
North Carolina	63.4	37926
North Dakota	60.5	46095
Ohio	63.7	41899
Oklahoma	63.6	41898
Oregon	62.7	45118
Pennsylvania	66.2	44192
Rhode Island	58.1	47654
South Carolina	67.2	37121
South Dakota	63.6	41846
Tennessee	64.1	36537
Texas	59.9	43495
Utah	69.1	54511
Vermont	68.6	48338
Virginia	65.1	56521
Washington	61.2	56412
West Virginia	71.0	36510
Wisconsin	64.9	47257
Wyoming	68.2	48490

The homeownership rate in the U.S. was 61.4% 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.

a-1. Estimate the model Ownership = β₀ + β₁Income + ε. (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.]

y^ = __ +__ Income

a-2. Interpret the model.

• For a $1000 increase in income homeownership rate is predicted to decrease by 0.01%.
• For a $1000 increase in income homeownership rate is predicted to decrease by 0.1%.
• For a $1000 increase in income homeownership rate is predicted to decrease by 0.001%.
• For a $1000 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.

• 0.88% of the sample variation in y is explained by the estimated regression equation.

• 0.88% of the sample variation in x is explained by the estimated regression equation.

• 2.12% of the sample variation in x is explained by the estimated regression equation.

• 0.12% of the sample variation in y is explained by the estimated regression equation.

Answer 1