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Price	Rooms	Neighborhood
309.6	7	0
307.4	8	0
340.3	9	0
346.5	12	0
298.2	6	0
337.8	9	0
324.1	10	0
313.2	8	0
327.8	9	0
325.3	8	0
308.5	6	1
381.3	13	1
337.4	10	1
346.2	10	1
342.4	9	1
323.7	8	1
329.6	8	1
343.6	9	1
360.7	11	1
348.3	9	1

1. Predict the selling price for a house with nine rooms that islocated in the east-side neighborhood. Construct a 95% confidenceinterval estimate and 95% prediction interval.
2. Perform a residual analysis on the results and determinewhether the regression assumptions are valid.
3. Is there a significant relationship between selling price andthe two independent variables (rooms and neighborhood) at the 0.05level of significance?
4. At the 0.05 level of significance, determine whether eachindependent variable makes a contribution to the regression model.Indicate the most appropriate regression model for this set ofdata.
5. Construct and interpret a 95% confidence interval estimate ofthe population slope for the relationship between selling price andnumber of rooms.
6. Construct and interpret a 95% confidence interval estimate ofthe population slope for the relationship between selling price andneighborhood.
7. Compute and interpret the adjusted r².
8. (omit…)
9. What assumption do you need to make about the slopeof selling price with number of rooms.
10. Add an interaction term to the model and, at the0.05 level of significance, determine whether it makes asignificant contribution to the model.
11. On the basis of the results of (f) and (l), which model is mostappropriate? Explain.