e sake prise ( in dollars) from the sas of the ose (sre The TH 243 equation of t
ID: 3317037 • Letter: E
Question
e sake prise ( in dollars) from the sas of the ose (sre The TH 243 equation of thct the regression line selling price- 9200 + sacofhme in a. The y-imtercept Explain your answer for this equation is (give units). Does it have a meaningful i The slope of the regression line is (give units) Interpret what the slope means in terms of THIS PROBLEM b. R for this regression was 73. What does an R' of 73 mcan in the specific terms of this poblem c. You look at a 2000 square foot house that costs $160,000. What does the equation predict for the selling price ofa 2000 square foot house ?ola Looking at your answer in pant c, what is the residual (eror) for the $160,000 home e Does your $160,000 home appear to be a good deal? Explain 2. Below is a residual plot from a different regression. You know from Chapters 89 that if a linear model is appropriac to model a relationship between 2 variables, we should see a certain type of pattem in the residuals Linear Model appropriate (yes or no)? If there is a problem, what is it? 3. The regression line that StatCrunch finds is also called a "least squares" line explain succiacly but an appropriate name for the lineExplanation / Answer
Solution
1) (a) The Y intercept for the given equation is 9200 dollars
Yes Y intercept have a meaningful interpretation as the intercept (the constant term) is the expected mean value of selling price when size of the house is 0 square feet i.e. only the land value
Slope = 77 dollars
Interpretation : with every 1 suare feet increase in size of house the selling price will increase by 77 dollars
(b) R2 = 0.73 i.e. 73% of the variability in selling price is being explained by the size of the house.
(c) selling price = 9200+77*2000 = 163,200 dollars
(d) residual error = 163,200-160,000 = 3,200 dollars
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