exam2_06s - MATH202 Spring 2006 Exam 2a Instructions: 1. Do...

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Unformatted text preview: MATH202 Spring 2006 Exam 2a Instructions: 1. Do not start until instructed to do so. 2. If you brought a cell phone by mistake, turn it off and place it under your seat. You may NOT use it as a calculator. 3. You may use a calculator (NOT a cell phone calculator) and a 3x5 card (front and back) with notes, but nothing else. 4. Code your UDelNet ID in the Last Name space on your scansheet and fill in the bubbles. 5. Write your name in the white space below the name box on your scansheet. 6. DO NOT put any part of your Social Security Number on your scansheet. 7. Choose the best answer to each question. 8. Use = .05. Questions 1 8 : A real estate agent wanted to develop a model to predict the selling price of a home. The agent believed that its size and style (Two-story, Side-split, Back-split, Ranch) are two important variables related to selling price. Let y = selling price (in thousands of dollars) 1 x = house size (in ft 2 ) 2 x = 1 if Two-story; 0 otherwise 3 x = 1 if Side-split; 0 otherwise 4 x = 1 if Back-split; 0 otherwise These data were collected for a sample of houses and the following regression models were fit to the data. Regression output for each model follows. Model A: + + + + + = 4 4 3 3 2 2 1 1 x x x x y Model B: + + + + = 4 4 3 3 2 2 x x x y Model C: + + + = 2 1 8 1 1 x x y Model D: + + + + + + + + = 4 1 7 3 1 6 2 1 5 4 4 3 3 2 2 1 1 x x x x x x x x x x y Model A Predictor Coef SE Coef T P Constant 27.48 11.58 2.37 0.020 x1 0.063341 0.005673 11.17 0.000 x2 20.341 6.878 2.96 0.004 x3 12.591 7.159 1.76 0.082 x4 19.325 7.783 2.48 0.015 S = 23.9637 R-Sq = 60.1% R-Sq(adj) = 58.4% Analysis of Variance Source DF SS MS F P Regression 4 82056 20514 35.72 0.000 Residual Error 95 54555 574 Total 99 136611 Model B Predictor Coef SE Coef T P Constant 141.232 8.316 16.98 0.000 x2 25.32 10.38 2.44 0.017 x3 4.60 10.77 0.43 0.670 x4 15.46 11.76 1.31 0.192 S = 36.2501 R-Sq = 7.7% R-Sq(adj) = 4.8% Analysis of Variance Source DF SS MS F P Regression 3 10460 3487 2.65 0.053 Residual Error 96 126151 1314 Total 99 136611 Model C Predictor Coef SE Coef T P Constant 90.10 40.25 2.24 0.027 x1 0.00932 0.04302 0.22 0.829 x1Sq 0.00001421 0.00001104 1.29 0.201 S = 24.7072 R-Sq = 56.7% R-Sq(adj) = Analysis of Variance Source DF SS MS F P Regression 2 77398 38699 63.39 0.000 Residual Error 97 59213 610 Total 99 136611 Model D Predictor Coef SE Coef T P Constant 36.73 21.76 1.69 0.095 x1 0.05819 0.01173 4.96 0.000 x2 -8.94 28.20 -0.32 0.752 x3 31.23 28.33 1.10 0.273 x4 -18.50 35.54 -0.52 0.604 x1x2 0.01584 0.01499 1.06 0.293 x1x3 -0.01155 0.01576 -0.73 0.466 x1x4 0.02162 0.01975 1.09 0.277 S = 23.7031 R-Sq = 62.2% R-Sq(adj) = 59.3% Analysis of Variance Source DF SS MS F P Regression 7 84922 12132 21.59 0.000 Residual Error 92 51689 562 Total 99 136611 2 x1 y 3000 2500 2000 1500 1000 250 200 150 100 50 Style Back-split Ranch Side-split Two-story Scatterplot of y vs x1 1. Which model is best described by the phrase parallel lines?Which model is best described by the phrase parallel lines?...
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exam2_06s - MATH202 Spring 2006 Exam 2a Instructions: 1. Do...

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