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# Samplefinal - STAT 2610 Final Exam Sample Name: _ Bubble in...

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STAT 2610 Final Exam Sample Name: _____________________________________ Bubble in the version of the exam you are doing in the space provided on your scantron sheet. In answering the questions, select the best alternative. The exam contains 42 questions. The following scenario will be applicable for all the questions on the exam. A real estate developer is in the beginning stages of planning a new residential subdivision. The developer believes that the subdivision will be perceived as a desirable place to live if houses do not stay on the market for very long. He would like you to identify features of houses that may result in quicker sales. He collects a sample of 80 house sales within the last two years and obtains information on each house contained in the following variables: Days_on_Mkt = Number of days house is listed for sale Sqft = Size of home in 100s of square feet Lux_items = Number of luxury items built into the home (ceramic tiles, hardwood floor, etc) Pool = Indicator of whether house a pool (1) or not (0) Below are examples of some observations from the sample. Pool SqFt(100s) Lux_Items Days_on_Mkt 0 18 1 28 0 18 2 34 0 16 5 18 0 20 6 14 0 21 2 29 0 24 3 27 1 20 2 42 1 23 3 48 1 25 4 45 1 28 2 56 1 29 5 48 1 30 4 68 An analyst uses multiple regression to predict the days_on_mkt of homes based on the three variables Pool, Sqft, and Lux_items Use the following Excel output to answer the next 12 questions. Regression Analysis 0.782 Adjusted R² 0.774 n 80 R 0.885 k 3 Std. Error 6.446 Dep. Var. Days_on_Mkt Cont’d on next page Page 1 of 12

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STAT 2610 Final Exam Sample ANOVA table Source SS df MS F p-value Regression 11,361.6598 3 3,787.2199 91.13 4.16E-25 Residual 3,158.2902 76 41.5564 Total 14,519.9500 79 Regression output confidence interval variables coefficients std. error t (df=111) p-value 95% lower 95% upper Intercept 7.5000 4.6771 1.604 .1130 -1.8152 16.8151 Pool 17.1024 1.4721 11.617 1.60E-18 14.1704 20.0344 SqFt(100s) 1.4299 0.1988 7.194 3.78E-10 1.0340 1.8258 Lux_Items -2.4891 0.4197 -5.930 8.37E-08 -3.3250 -1.6531 Predicted values for: Days_on_Mkt 95% Confidence Interval 95% Prediction Interval Pool SqFt(100s) Lux_Item s Predicted lower upper lower upper Leverag e 1 25 2 55.371 53.137 57.606 42.339 68.403 0.030 0 25 2 38.269 35.759 40.779 25.187 51.351 0.038 1. What is the best interpretation for the regression coefficient of the independent variable Pool? a. When comparing two houses having the same square footage and number of luxury features, a home with a pool is predicted to be on market for 1710 more days than a home without a pool, on average. b. When comparing any two houses, a home with a pool is predicted to be on market for 1710 more days than a home without a pool, on average. c.
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## This note was uploaded on 09/18/2011 for the course STAT 2610 taught by Professor Syvantek during the Spring '08 term at Auburn University.

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Samplefinal - STAT 2610 Final Exam Sample Name: _ Bubble in...

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