The data stored in Housing compares the sale price (in thousands $) of a sample of homes in a local county with the assessed value of those homes calculated prior to the sale. Conduct a regression where the Assessed Value of the home is the independent variable used to predict the house sale price (Price).

a) Interpret the slope coefficient, β1

b) Explain why the intercept term (β0) does not have a meaningful interpretation.

c) Is the population relationship between the assessed value of the house and the house price statistically different from zero? Conduct a hypothesis test to answer this question.

d) Is the population relationship between the assessed value of the house and the house price is such that a one-dollar increase in the assessed value of the house will result in a 1.95 dollar increase in the house price? Conduct a hypothesis test to answer this question.

e) Is the population relationship between the assessed value of the house and the house price is such that a one-dollar increase in the assessed value of the house will result in LESS THAN a 1.95 dollar increase in the house price? Conduct a hypothesis test to answer this question.

f) Is the population relationship between the assessed value of the house and the house price is such that a one-dollar increase in the assessed value of the house will result in MORE THAN a 1.60 dollar increase in the house price? Conduct a hypothesis test to answer this question.

Housing data:

Price	Assessed
194.10	178.17
201.90	180.24
188.65	174.03
215.50	186.31
187.50	175.22
172.00	165.54
191.50	172.43
213.90	185.61
169.34	160.80
196.90	181.88
196.00	179.11
161.90	159.93
193.00	175.27
209.50	185.88
193.75	176.64
206.70	184.36
181.50	172.94
194.50	176.50
169.00	166.28
196.90	179.74
186.50	172.78
197.90	177.90
183.00	174.31
197.30	179.85
200.80	184.78
197.90	181.61
190.50	174.92
197.00	179.98
192.00	177.96
195.90	179.07

Answer rating: 100% (QA)

Answer The data is exported to R first and then the linear model i... View the full answer