M3 Group Assignment Instructions Complete the Assignment, name it as GroupXX_Assign3.xls (where XX is your Group Name), and upload and submit to the instructor through Dropbox. Do not enter anything in the spreadsheet cells that are black, labeled \"Grader\". You must complete this assignment without the assistance of persons other than the members of your Group. You may use any other resources you deem necessary. Answer the questions below by placing the appropriate graph and/or answers in the designated cells of the spreadsheet. DO NOT CHANGE THE APPEARANCE OR FUNCTIONALITY OF THE SPREADSHEET UNLESS INSTRUCTED TO DO SO. Question 1 (20 points) A mental health agency measured the self-esteem score for randomly selected individuals with disabilities who were involved in some work activity within the past year. The spreadsheet named Self Esteem provides the data including each individuals self-esteem measure (y), years of education (YrsEdu), age, months worked in the last 6 years (MonWork), marital status dummy variables (MS2, MS3, MS4) indicating if the individual is single, married, separated, or divorced, and a support level (SL) dummy variable indicating if the level of job support (counseling, etc) was provided directly (1) or indirectly (0). Regarding marital status, if single all MS indicators are 0, while MS2 = 1 indicates married, MS3 = 1 indicates separated, and MS4 = 1 indicates divorced. a. 3 points: In cell N4, use Excel's \"Correlation\" Data Analysis tool to construct a correlation matrix for all the variables. Note that the categories in columns I and J should not be included since the data are already represented as dummy variables in columns E through H. b. 3 points: Considering the correlation between self-esteem and each x variable identify the three variables that, based on correlation with y alone, should be considered as best candidates for inclusion in the model. Shade the appropriate cells containing the correlation values in yellow. Ignore any multicollinearity concerns for this part. c. 3 points: With cell N19 as the upper left hand corner of the output, fit the full regression model. (Do not include a residual plot) d. 4 points: Considering the regression output from part c, shade (in yellow) the name of any x variable that appears significant and should remain in the model. Also shade the t stat and p-value. Consider the p-value small if it is less than 0.05. e. 3 points: Partial Regression Model: With cell N51 the upper left hand corner of the output, fit the model including only the x variable(s) that were found to be significant in part d. (Do not include a residual plot) f. 4 points: Comment on the impact of each independent variable in the partial regression model from part e on Self Esteem. Provide your comments in Cells N66:T78. 1 Question 2 (15 points) A bank must prepare for a discrimination suit filed on behalf of female employees that claim females are paid less than male employees. The bank manager sampled employee files to see if he could build a useful model for predicting salary as a function of gender and other characteristics. For each employee, the data includes salary (y, in thousands of dollars), years experience (YrsExp), years prior experience (YrsPrior), and Gender. The data is in the spreadsheet named Bank. a. 3 points: Since Gender is a categorical variable, construct the appropriate dummy variable in column E to indicate gender as female = 1 and male = 0. You must use an \"IF\" statement in the appropriate cell(s) to indicate the correct dummy value based on gender. b. 4 points: With cell H7 the upper left hand corner of the output, fit the full model. (Do not include a residual plot). c. 3 points: Based on the regression output from part b, shade (in yellow) the name of any x variable that appears significant and should remain in the model. Also shade the t stat and p-value. d. 5 points: Based on your analysis, what is your assessment of the lawsuit? Does it look promising for the bank? What additional variables need to be included in the model to strengthen the validity of the model? Place your comments in Cells H33:P45. Question 3 (15 points) The trend in home building in recent years has been to emphasize open spaces and great rooms, rather than smaller living rooms and family rooms. A home builder has been building such homes, but his homes had been taking many months to sell and selling for substantially less than the asking price. In order to determine what types of homes would attract residents; the builder contacted your team. The spreadsheet named Builder contains the sales price y, square footage X1, number of rooms X2, number of bedrooms X3, and age X4 for each of 63 single-family residences recently sold. Perform a regression analysis of the data. a. b. 5 points: With cell I5 as the upper left hand corner of the output, fit the full regression model. Identify the significant coefficients. 10 points: Make recommendations to the builder in Cells I30:Q43 on how to increase sales price by adjusting house layout. For example, will it be more profitable to build a house with smaller living room given a fixed square footage? How about smaller family room or a larger great room? Will it be wise to increase the number of bedrooms? Question 4 (20 points) A company sells products in several sales territories, each of which is assigned to a single sales rep. The spreadsheet named Sales contains 25 observations on eight independent variables. A regression analysis needs to be conducted to determine whether a variety of predictor variables could explain sales in each territory. To compute all possible regression models, we could develop 8 one-variable equations, 28 two variable regression equations, and so on. As a matter of fact, a total of 255 different estimated regression equations can be modeled. Next try three advanced regression techniques in StatTools. Enter 0.05 in the p-value to Enter or Leave box. Variable Sales Time Poten AdvExp Share Change Accounts Definition Total sales credited to the sales rep Length of time employed in month Market potential; total industry sales in units for the sales territory Advertising expenditure in the sales territory Market share; weighted average for the past four years Change in the market share over the previous four years Number of accounts assigned to the sale rep 2 Work Rating a. b. c. d. Workload; a weighted index based on annual purchases and concentrations of accounts Sales rep overall rating on eight performance dimension; an aggregate rating on a 1-7 scale 5 points: With Cell K4 as the upper left hand corner of the output, fit the full regression model (report Regression Table only) using the Stepwise Regression function in StatTools. 5 points: With Cell K15 as the upper left hand corner of the output, fit the full regression model (report Regression Table only) using the Forward Selection function in StatTools. 5 points: With Cell K26 as the upper left hand corner of the output, fit the full regression model (report Regression Table only) using the Backward Elimination function in StatTools. 5 points: Did the three different methods reach the same model? If not, apply your managerial judgment to choose one model that you think is the best. State your reasons. Place your answers in Cells K37:T48. Question 5 (30 points) To measure value, Consumer Reports developed a statistic referred as a value score. The value score is based upon five-year owner costs, overall road-test scores, and predicted-reliability ratings. Five-year owner costs are based upon the expenses incurred in the first five years of ownership, including depreciation, fuel, maintenance and repairs, and so on. Using a national average of 12,000 miles per year, an average cost per mile driven is used as the measure of five-year owner costs. Road-test scores are the results of more than 50 tests and evaluations and are based on a 100-point scale, with higher score indicating better performance, comfort, convenience, and fuel economy. The highest road-test score obtained in the tests conducted by Consumer Reports was a 99 for a Lexus LS 460L. Predicted-reliability ratings (1=Poor, 2=Fair, 3=Good, 4=Very Good, and 5=Excellent) are based upon data from Consumer Reports' Annual Auto Survey. A car with a value score of 1.0 is considered to be an \"average-value\" car. A car with a value score of 2.0 is considered to be twice as good a value as a car with a value score of 1.0; a car with a value score of 0.5 is considered half as good as average; and so on. The data for three sizes of cars (13 small sedans, 20 family sedans, and 21 upscale sedans), including price ($) of each car tested, are provided in spreadsheet Car (Consumer Reports, April, 2012). a. 5 points: To incorporate the effect of size of a car, create two dummy variables in Columns H and I using the following coding. Family-Sedan: 1 if the car is a family sedan and 0 otherwise. Upscale-Sedan: 1 if the car is an upscale sedan and 0 otherwise. b. 7.5 points: First treating Cost/Mile as the dependent variable, develop an estimated regression with Family-Sedan and Upscale-Sedan as the independent variables. With Cell K3 as the upper left hand corner of the output, fit the full regression model (report Regression Table only). Summarize your model in Cells K12:S20. Are the coefficients significant? Interpret the coefficients. c. 7.5 points: Next treating Value Score as the dependent variable, develop an estimated regression equation using all other variables as the independent variables. Choose Stepwise as the Regression Type. With Cell K26 as the upper left hand corner of the output, fit the full regression model (report Regression Table only). Does your model support the claim that \"smaller car provide better values than larger cars?\" The Small Sedans represent the smallest type of car and the Upscale Sedans represent the largest type of car. State your reasons in Cells K39:S47. d. 5 points: Using the model developed in part c, calculated the predicted Value Score in Column J. Which car has the smallest Value Score residual and which car has the largest Value Score residual? e. 5 points: Place the Residual Plot for the model developed in part c in Cells K62:S78. Are the assumptions being satisfied? Is the variance of the error terms constant? Are residuals scattered randomly around zero? Place your assessments in Cells K80:S88. e. in in the model. Also shade the t stat and p-value. 3 y X2 X3 X1 Self Esteem YrsEdu Age MonWork 2 9 52 4 2 9 52 4 3 11 40 14 3 9 46 10 3 12 40 12 3 10 47 6 3 10 50 4 3 10 44 5 3 9 46 9 3 9 47 4 3 10 51 4 3 9 47 11 3 9 51 10 3 10 42 12 3 9 48 9 3 9 46 3 3 12 37 14 3 12 35 13 3 9 43 3 3 10 45 4 3 10 50 10 3 9 46 8 3 11 49 2 3 12 48 7 3 10 45 8 3 9 47 9 3 9 46 6 3 9 47 4 3 10 45 3 3 10 47 2 4 13 28 12 4 12 42 37 4 10 40 23 4 12 38 23 4 9 45 10 4 10 47 10 4 9 47 9 4 12 39 23 4 10 43 12 4 11 39 21 4 12 33 10 4 12 35 11 4 12 45 14 4 13 41 12 4 9 43 5 5 12 28 51 5 14 32 40 5 14 38 29 5 14 36 29 5 14 39 29 5 13 39 21 5 9 48 7 X4 MS2 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 X5 MS3 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 X6 MS4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 X7 SL 0 0 1 1 0 0 0 0 1 0 0 1 1 1 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 0 1 0 0 0 0 0 0 1 1 1 1 1 1 1 5 5 5 5 6 6 6 6 12 13 14 13 12 12 16 14 29 26 30 26 27 38 28 38 24 32 37 31 58 17 61 64 1 1 0 0 0 0 1 0 0 0 1 0 0 0 0 1 0 0 0 1 0 0 0 0 1 1 1 1 1 0 1 1 Categorical Variables SL MS None Single None Single Direct Single Direct Single None Single None Single None Single None Single Direct Married None Married None Married Direct Separated Direct Separated Direct Separated Direct Separated None Separated None Separated None Separated None Separated None Separated Direct Divorced None Divorced None Divorced None Divorced None Divorced None Divorced None Divorced None Divorced None Divorced None Divorced Direct Single Direct Single Direct Single Direct Single Direct Single Direct Single Direct Single None Married Direct Separated None Separated None Separated None Separated None Divorced None Divorced None Divorced Direct Single Direct Single Direct Single Direct Single Direct Single Direct Single Direct Married Question 1 Part c d Grader Part e Grader Direct Direct Direct Direct Direct None Direct Direct Married Married Separated Divorced Single Single Married Separated Part f Grader Part Grader a b y variable Salary: current annual salary in thousands of dollars. x variables YrsExp: years experience with this Bbank YrsPrior: number of years prior work experience at another bank. Gender: (categorical), 1 = Female, 0 = Male Bank salary data Employee 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 Salary YrsExp 32 6 39.1 17 33.2 15 30.6 11 29 6 30.5 6 30 7 27 11 34 7 29.5 12 26.8 12 31.3 11 31.2 12 34.7 13 30 7 31 6 27 9 29.6 11 32.6 8 29.6 7 29.5 7 31 6 28.5 8 26.7 6 30.75 6 29.5 6 42.2 19 37.6 16 34 15 33 7 28.76 10 35.4 14 31 6 38.8 21 34.3 17 35 22 34.6 6 28.5 5 29.5 14 30.5 6 34.2 8 43.6 18 33.5 10 33 15 YrsPrior 1 1 0 7 0 0 0 2 0 0 2 8 0 6 0 0 0 9 6 3 2 3 0 4 1 1 6 0 6 7 4 0 8 2 0 0 2 4 0 2 1 0 0 1 Gender Male Female Female Female Male Female Female Male Female Female Female Female Female Female Female Female Female Female Female Female Female Male Female Male Male Male Female Female Female Female Female Female Male Female Female Female Female Female Female Male Female Female Female Female Question 2: Part Grader a b c Part d Grader 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 45.3 38.8 29.9 31.2 34 30.45 35.5 34 29.1 29.65 29.2 29.8 33.5 34 29.6 34 37.25 33 28.6 36 37.3 29.9 31.5 41.4 32.74 33.5 32 30.8 42 34 32.5 31.7 36.5 33 31.2 34 33 33.9 39 34.92 39 34 31.9 37 34 36.4 38.2 35.3 34.5 30.5 30 37.3 40.2 35.5 21 20 13 8 18 5 6 7 10 11 18 12 19 11 12 21 6 9 7 8 7 10 14 8 20 6 8 12 6 7 19 12 6 7 11 11 9 7 6 15 6 11 9 6 7 6 18 18 6 15 5 11 8 8 0 3 0 10 0 0 3 10 0 0 1 0 0 0 0 0 8 3 0 1 4 4 8 4 5 1 9 0 3 0 0 10 0 0 0 0 0 4 9 18 5 0 7 1 0 2 1 0 2 0 2 0 0 0 Female Male Female Male Female Female Male Female Female Female Female Female Female Female Female Female Female Male Female Female Female Male Female Female Female Male Female Female Female Male Female Female Male Male Female Female Female Female Female Male Male Female Female Male Male Female Female Female Male Female Male Female Female Male 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 35 38 35.3 34.1 43.2 36.1 34.6 36 36.2 37.5 41 35.6 39.8 41.3 42.5 45.8 34.9 41.5 38 35 40 36 33.7 36.3 38 39.5 36.3 32.5 37 32.6 36 35 43.6 33.8 35.3 42.4 39.5 43.5 42 40.3 44 40.66 39.7 45 43.9 38 39.02 44.5 41 44 44 42.5 40.26 44.5 14 7 12 17 7 18 10 8 10 10 7 13 8 14 12 7 8 7 8 9 9 8 12 8 6 7 10 11 15 6 7 6 6 11 24 19 8 28 9 24 9 28 16 9 10 11 8 8 7 9 9 8 10 8 0 3 0 0 5 5 3 0 2 0 12 0 5 4 7 8 6 0 0 0 0 0 0 4 2 0 5 2 6 1 0 0 5 0 0 6 0 10 1 9 5 2 1 5 0 3 3 3 1 3 0 4 3 1 Female Female Female Female Female Female Female Male Female Female Female Female Female Female Female Female Female Male Female Female Female Male Female Male Female Female Female Female Female Female Female Female Female Female Female Female Male Female Male Female Male Female Female Female Female Female Female Male Male Male Male Female Female Male 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 35.5 42.5 44 45 44.4 38 41.8 45.5 42.5 44 54.3 44.8 47 43.8 48 42.7 48.5 42 45.5 44.5 51.2 47.5 44.5 47 47 43.1 49 48.5 45 52.5 47.5 48 46.5 61.5 50 61.8 43 47 58.5 55 57 57 60 60 59 60 65 52 58 60 74 95 97 88 16 9 10 9 18 20 7 26 8 6 22 29 9 18 15 12 17 19 19 14 16 10 11 11 9 20 11 11 11 19 9 10 11 15 12 15 19 14 12 19 27 20 17 16 22 15 23 23 25 24 42 37 39 35 9 0 0 2 4 0 0 0 4 12 8 0 4 0 4 0 1 0 1 0 2 0 0 0 10 4 2 0 5 5 2 0 4 2 2 2 0 1 6 7 3 1 0 0 4 0 0 1 0 0 0 0 0 0 Female Male Female Male Female Female Male Male Male Female Female Female Male Female Female Female Female Female Female Female Female Male Female Male Male Female Male Male Female Female Male Male Male Female Female Female Female Male Female Male Male Male Male Male Male Male Male Male Male Male Male Male Male Male 207 208 94 30 38 36 0 0 Male Female Measurements taken on 63 single-family residences Residence 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 sales price (x $1,000) Y 53.5 49.0 50.5 49.9 52.0 55.0 80.5 86.0 69.0 149.0 46.0 38.0 49.5 105.0 152.5 85.0 60.0 58.5 101.0 79.4 125.0 87.9 80.0 94.0 74.0 69.0 63.0 67.5 35.0 142.5 92.2 56.0 63.0 60.0 34.0 52.0 75.0 93.0 60.0 73.0 71.0 83.0 90.0 83.0 115.0 50.0 55.2 61.0 147.0 210.0 60.0 100.0 square feet X1 1008 1290 860 912 1204 1204 1764 1600 1255 3600 864 720 1008 1950 2086 2011 1465 1232 1736 1296 1996 1874 1580 1920 1430 1486 1008 1282 1134 2400 1701 1020 1053 1728 416 1040 1496 1936 1904 1080 1768 1503 1736 1695 2186 888 1120 1400 2165 2353 1536 1972 rooms X2 5 6 8 5 6 5 8 7 5 10 5 4 6 8 7 9 6 5 7 6 7 5 5 5 9 6 5 5 5 9 5 6 5 6 3 5 6 8 7 5 8 6 7 6 8 5 6 5 7 8 6 8 bedrooms X3 2 3 2 3 3 3 4 3 3 5 3 2 3 3 3 4 3 2 3 3 3 2 3 3 3 3 2 3 2 4 3 3 2 3 1 2 3 4 4 2 4 3 3 3 4 2 3 3 3 4 3 3 age X4 35 36 36 41 40 10 64 19 16 17 37 41 35 52 12 76 102 69 67 11 9 14 11 14 16 27 35 20 74 15 15 16 24 26 42 9 30 39 32 24 74 14 16 12 12 34 29 33 2 15 36 37 53 54 55 56 57 58 59 60 61 62 63 44.5 55.0 53.4 65.0 73.0 40.0 141.0 68.0 139.0 140.0 55.0 1120 1664 925 1288 1400 1376 2038 1572 1545 1993 1130 5 7 5 5 5 6 12 6 6 6 5 3 3 3 3 3 3 4 3 3 3 2 27 79 20 2 2 103 62 29 9 4 21 Question 3: Part a Part b Sales 3669.88 3473.95 2295.1 4675.56 6125.96 2134.94 5031.66 3367.45 6519.45 4876.37 2468.27 2533.31 2408.11 2337.38 4586.95 2729.24 3289.4 2800.78 3264.2 3453.62 1741.45 2035.75 1578 4167.44 2799.97 Time 43.1 108.13 13.82 186.18 161.79 8.94 365.04 220.32 127.64 105.69 57.72 23.58 13.82 13.82 86.99 165.85 116.26 42.28 52.84 165.04 10.57 13.82 8.13 58.44 21.14 Poten 74065.1 58117.3 21118.5 68521.3 57805.1 37806.9 50935.3 35602.1 46176.8 42053.2 36829.7 33612.7 21412.8 20416.9 36272 23093.3 26878.6 39572 51866.1 58749.8 23990.8 25694.9 23736.3 34314.3 22809.5 AdvExp 4582.9 5539.8 2950.4 2243.1 7747.1 402.4 3140.6 2086.2 8846.2 5673.1 2761.8 1991.8 1971.5 1737.4 10694.2 8618.6 7747.9 4565.8 6022.7 3721.1 861 3571.5 2845.5 5060.1 3552 Share 2.51 5.51 10.91 8.27 9.15 5.51 8.54 7.07 12.54 8.85 5.38 5.43 8.48 7.8 10.34 5.15 6.64 5.45 6.31 6.35 7.37 8.39 5.15 12.88 9.14 Change Accounts 0.34 74.86 0.15 107.32 -0.72 96.75 0.17 195.12 0.5 180.44 0.15 104.88 0.55 256.1 -0.49 126.83 1.24 203.25 0.31 119.51 0.37 116.26 -0.65 142.28 0.64 89.43 1.01 84.55 0.11 119.51 0.04 80.49 0.68 136.58 0.66 78.86 -0.1 136.58 -0.03 138.21 -1.63 75.61 -0.43 102.44 0.04 76.42 0.22 136.58 -0.74 88.62 Work 15.05 19.97 17.34 13.4 17.64 16.22 18.8 19.86 17.42 21.41 16.32 14.51 19.35 20.02 15.26 15.87 7.81 16 17.44 17.98 20.99 21.66 21.46 24.78 24.96 Rating 4.9 5.1 2.9 3.4 4.6 4.5 4.6 2.3 4.9 2.8 3.1 4.2 4.3 4.2 5.5 3.6 3.4 4.2 3.6 3.1 1.6 3.4 2.7 2.8 3.9 Question 4: Part a Part b Part c Part d Car Toyota Corolla (base, manual) Mazda3 i Touring (manual) Toyota Corolla LE Mazda3 i Touring Hyundai Elantra GLS Nissan Sentra 2.0 SL Kia Forte Sedan EX Ford Focus SE Ford Fiesta SE Volkswagen Jetta SE (2.5) Volkswagen Jetta TDI Chevrolet Cruze LS (1.8) Chevrolet Cruze 1LT (1.4T) Nissan Altima 2.5 S (4-cyl.) Kia Optima LX (2.4) Subaru Legacy 2.5i Premium Ford Fusion Hybrid Honda Accord LX-P (4-cyl.) Mazda6 i Sport (4-cyl.) Hyundai Sonata GLS (2.4) Ford Fusion SE (4-cyl.) Chevrolet Malibu LT (4-cyl.) Kia Optima SX (2.0T) Ford Fusion SEL (V6) Nissan Altima 3.5 SR (V6) Hyundai Sonata Limited (2.0T) Honda Accord EX-L (V6) Mazda6 s Grand Touring (V6) Ford Fusion SEL (V6, AWD) Subaru Legacy 3.6R Limited Chevrolet Malibu LTZ (V6) Chrysler 200 Limited (V6) Chevrolet Impala LT (3.6) Lexus ES 350 Acura TL (base) Lexus IS 250 Infiniti G25 Journey Lexus HS 250h Premium Acura TSX (4-cyl.) Infiniti G37 Journey Toyota Avalon Limited Hyundai Genesis 3.8 Volvo S60 T5 Nissan Maxima 3.5 SV Buick Regal CXL (2.4) Lincoln MKZ BMW 328i Audi A4 Premium Quattro Ford Taurus Limited Buick Regal CXL (turbo) Mercedes-Benz C300 Sport Volkswagen CC Luxury (2.0T) Saab 9-3 2.0T Buick LaCrosse CXS (V6) Size Small Sedan Small Sedan Small Sedan Small Sedan Small Sedan Small Sedan Small Sedan Small Sedan Small Sedan Small Sedan Small Sedan Small Sedan Small Sedan Family Sedan Family Sedan Family Sedan Family Sedan Family Sedan Family Sedan Family Sedan Family Sedan Family Sedan Family Sedan Family Sedan Family Sedan Family Sedan Family Sedan Family Sedan Family Sedan Family Sedan Family Sedan Family Sedan Family Sedan Upscale Sedan Upscale Sedan Upscale Sedan Upscale Sedan Upscale Sedan Upscale Sedan Upscale Sedan Upscale Sedan Upscale Sedan Upscale Sedan Upscale Sedan Upscale Sedan Upscale Sedan Upscale Sedan Upscale Sedan Upscale Sedan Upscale Sedan Upscale Sedan Upscale Sedan Upscale Sedan Upscale Sedan Price ($) Cost/Mile Road-Test Score 16,419 18,895 18,404 19,745 18,445 20,150 19,040 20,280 16,595 20,300 25,100 18,375 20,530 23,970 21,885 23,830 32,360 23,730 22,035 21,800 23,625 24,115 29,050 28,400 30,335 28,090 28,695 30,790 30,055 30,094 28,045 27,825 28,995 38,615 36,465 33,734 34,225 38,939 29,675 37,225 35,485 39,850 35,100 33,700 28,840 37,160 39,175 35,895 34,980 32,135 37,325 32,680 31,615 37,555 0.44 0.50 0.47 0.52 0.53 0.57 0.57 0.52 0.47 0.54 0.50 0.57 0.60 0.59 0.58 0.59 0.63 0.56 0.58 0.56 0.57 0.57 0.72 0.67 0.69 0.66 0.67 0.74 0.71 0.71 0.67 0.70 0.67 0.77 0.75 0.75 0.73 0.75 0.67 0.79 0.73 0.78 0.76 0.78 0.65 0.80 0.79 0.76 0.78 0.71 0.83 0.73 0.70 0.81 70 74 71 70 80 74 71 68 61 60 68 67 69 91 81 83 84 80 73 89 76 74 84 80 93 89 90 81 75 88 83 52 63 91 82 84 86 83 84 95 86 92 77 83 77 77 77 76 73 79 77 82 69 74 Predicted Reliability Value Score 4 5 4 5 3 4 3 2 2 3 2 1 1 4 4 4 5 4 4 3 4 3 4 4 4 3 3 4 4 3 3 5 3 5 5 5 4 4 3 4 3 3 4 3 2 4 3 3 3 2 3 2 3 2 1.99 1.94 1.89 1.82 1.64 1.51 1.32 1.30 1.25 1.24 1.18 0.96 0.91 1.75 1.73 1.73 1.70 1.62 1.60 1.58 1.55 1.48 1.43 1.42 1.42 1.39 1.36 1.34 1.32 1.29 1.20 1.20 1.05 1.45 1.41 1.40 1.37 1.36 1.35 1.33 1.27 1.22 1.18 1.17 1.14 1.12 1.10 1.08 1.07 1.06 1.04 1.04 1.00 0.82 Part a Part b Part c Smallest Largest Part d Part e