Project Description:

you want to develope a model to predict the selling price of homes based on assessed value. a sample of 30 recently sold single-family houses in a small city is selected to study the relationship between selling price (in thousands of dollars) and assessed value (in thousands of dollars). the houses in the city were reassessed at full value one year prior to the study. the results are in the attached data.
(hint: first determine which are the independent and dependent variables)

a) construct a scatter plot and, assuming a linear relationship, use the least-squares method to compute the regression coefficients b0 and b1.

b) interpret the meaning of the y intercept, b0, and the slope,b1, in this problem.

c) use the prediction line developed in (a) to predict the selliing price for a house whose assessed value is $170,000

d) determine the coeffient of determination, r2, and interpret its meaning in this problem.

e) perform a residual analysis on your results and evaluate the regression assumptions.

f) at the 0.05 level of significance, is there evidence of a linear relationship between selling price and assessed value?

g) construct a 95% confidence intreval estimate of the population slope.
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Project Stats:

Price Type: Negotiable

Total Proposals: 2
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