,1) FOOTBALL PLAYER RATINGS, ,The data appearing in Table 1 show the rating for 25 NFL prospects along with their position, weight, speed (time in 40 yard dash in seconds)., ,Table 1. Player ratings and performance data, , , ,Name, , , ,Position, , , ,Weight, , , ,Speed, , , ,Rating, , , ,Cosey Coleman, , , ,Guard, , , ,322, , , ,5.38, , , ,7.4, , , ,Travis Claridge, , , ,Guard, , , ,303, , , ,5.18, , , ,7, , , ,Kaulana Noa, , , ,Guard, , , ,317, , , ,5.34, , , ,6.8, , , ,Leander Jordan, , , ,Guard, , , ,330, , , ,5.46, , , ,6.7, , , ,Chad Clifton, , , ,Guard, , , ,334, , , ,5.18, , , ,6.3, , , ,Manula Savea, , , ,Guard, , , ,308, , , ,5.32, , , ,6.1, , , ,Ryan Johanningmei, , , ,Guard, , , ,310, , , ,5.28, , , ,6, , , ,Mark Tauscher, , , ,Guard, , , ,318, , , ,5.37, , , ,6, , , ,Blaine Saipaia, , , ,Guard, , , ,321, , , ,5.25, , , ,6, , , ,Richard Mercier, , , ,Guard, , , ,295, , , ,5.34, , , ,5.8, , , ,Damion McIntosh, , , ,Guard, , , ,328, , , ,5.31, , , ,5.3, , , ,Jeno James, , , ,Guard, , , ,320, , , ,5.64, , , ,5, , , ,Al Jackson, , , ,Guard, , , ,304, , , ,5.2, , , ,5, , , ,Chris Samuels, , , ,Offensive tackle, , , ,325, , , ,4.95, , , ,8.5, , , ,Stockar McDougle, , , ,Offensive tackle, , , ,361, , , ,5.5, , , ,8, , , ,Chris McIngosh, , , ,Offensive tackle, , , ,315, , , ,5.39, , , ,7.8, , , ,Adrian Klemm, , , ,Offensive tackle, , , ,307, , , ,4.98, , , ,7.6, , , ,Todd Wade, , , ,Offensive tackle, , , ,326, , , ,5.2, , , ,7.3, , , ,Marvel Smith, , , ,Offensive tackle, , , ,320, , , ,5.36, , , ,7.1, , , ,Michael Thompson, , , ,Offensive tackle, , , ,287, , , ,5.05, , , ,6.8, , , ,Bobby Wiliams, , , ,Offensive tackle, , , ,332, , , ,5.26, , , ,6.8, , , ,Darnell Alford, , , ,Offensive tackle, , , ,334, , , ,5.55, , , ,6.4, , , ,Terrance Beadles, , , ,Offensive tackle, , , ,312, , , ,5.15, , , ,6.3, , , ,Tutan Reyes, , , ,Offensive tackle, , , ,299, , , ,5.35, , , ,6.1, , , ,Greg Robinson-Ran, , , ,Offensive tackle, , , ,333, , , ,5.59, , , ,6, , , ,Develop a regression model explaining the rating using the factors position, weight and speed. Use guard as the base for position., ,Which factors (independent variables) are significant using an ? = 0.05?, ,Develop a point estimate and a 95% confidence interval for the rating for an offensive tackle weighing 300 who ran the 40 in 5.1 seconds., ,Comments and Hints:, ,Do all work in a single worksheet.,Specify output range of regression output for first model as J1. Shade the cell or cells holding the P-value(s) corresponding to factor(s) that are significant using an ? = 0.05.,Do all estimations in columns A through H beginning in row 30.,2) ,AUTO REPAIR TIMES, ,The data appearing in table 1 show the length of time required for autos brought in for repair and the corresponding number of months since last service, the type of service and the repairperson., , ,Table 1. Repair times and associated factors, , , ,Months Since Last Service, , , ,Type of Repair, , , ,Repairperson, , , ,Repair Time In Hours, , , ,4, , , ,Electrical, , , ,Bob, , , ,5.0, , , ,8, , , ,Electrical, , , ,Tom, , , ,7.5, , , ,10, , , ,Electrical, , , ,Tom, , , ,8.4, , , ,2, , , ,Mechanical, , , ,Tom, , , ,3.3, , , ,1, , , ,Mechanical, , , ,Tom, , , ,3.7, , , ,5, , , ,Electrical, , , ,Bob, , , ,5.0, , , ,7, , , ,Mechanical, , , ,Dave, , , ,7.3, , , ,7, , , ,Electrical, , , ,Bob, , , ,5.8, , , ,10, , , ,Electrical, , , ,Tom, , , ,8.0, , , ,5, , , ,Electrical, , , ,Tom, , , ,5.8, , , ,10, , , ,Mechanical, , , ,Bob, , , ,10.1, , , ,6, , , ,Electrical, , , ,Tom, , , ,5.6, , , ,4, , , ,Electrical, , , ,Dave, , , ,6.3, , , ,6, , , ,Mechanical, , , ,Dave, , , ,7.4, , , ,1, , , ,Mechanical, , , ,Tom, , , ,4.3, , , ,10, , , ,Electrical, , , ,Dave, , , ,8.7, , , ,5, , , ,Electrical, , , ,Tom, , , ,4.4, , , ,2, , , ,Electrical, , , ,Tom, , , ,4.0, , , ,9, , , ,Electrical, , , ,Dave, , , ,7.8, , , ,1, , , ,Mechanical, , , ,Bob, , , ,4.3, , , ,7, , , ,Mechanical, , , ,Bob, , , ,7.8, , , ,5, , , ,Electrical, , , ,Dave, , , ,5.4, , , ,4, , , ,Mechanical, , , ,Tom, , , ,5.0, , , ,6, , , ,Mechanical, , , ,Dave, , , ,7.8, , , ,1, , , ,Electrical, , , ,Bob, , , ,3.9, , , ,2, , , ,Mechanical, , , ,Dave, , , ,5.2, , , ,3, , , ,Mechanical, , , ,Tom, , , ,5.2, , , ,2, , , ,Mechanical, , , ,Tom, , , ,3.3, , , ,9, , , ,Electrical, , , ,Bob, , , ,7.0, , , ,3, , , ,Electrical, , , ,Dave, , , ,5.4, , , ,4, , , ,Mechanical, , , ,Bob, , , ,5.4, , , ,5, , , ,Electrical, , , ,Tom, , , ,5.9, , , ,Develop a regression model explaining the repair time based upon the number of months since last repair, the type of repair and the repair person. Use electrical as the base for type of repair and Dave as the base for repairperson., ,Develop a simpler regression model by eliminating any factor (independent variable) that is not significant using an ? = 0.05., ,Using both models above, generate a point estimate and a 95% confidence interval on the repair time for an auto which was last serviced 5 months ago which requires electrical repair assuming Tom is the repair person., , ,Comments and Hints:, ,Do all work in a single worksheet, ,Specify output range of regression output for first model as J1. Shade the cell or cells holding the P-value(s) for factor(s) to be eliminated., ,Specify the output range of regression output for second model as J25., ,Do all estimations in columns A through H beginning in row 37.,3) ,TRUCK RESALE VALUE,Table 1 shows data for various truck models., ,Table 1. Vehicle type, suggested retail price and resale value, , , ,Vehicle, , , ,Type of Vehicle, , , ,Suggested Retail Price ($1000), , , ,Resale Value (%), , , ,Chevrolet Blazer LS, , , ,Sport Utility, , , ,19.495, , , ,55, , , ,Ford Explorer Sport, , , ,Sport Utility, , , ,20.495, , , ,57, , , ,GMC Yukon XL 1500, , , ,Sport Utility, , , ,26.789, , , ,67, , , ,Honda CR-V, , , ,Sport Utility, , , ,18.965, , , ,65, , , ,Isuzu VehiCross, , , ,Sport Utility, , , ,30.186, , , ,62, , , ,Jeep Cherokee Limited, , , ,Sport Utility, , , ,25.745, , , ,57, , , ,Mercury Mountaineer Monterrey, , , ,Sport Utility, , , ,29.895, , , ,59, , , ,Nissan Pathfinder XE, , , ,Sport Utility, , , ,26.919, , , ,54, , , ,Toyota 4Runner, , , ,Sport Utility, , , ,22.418, , , ,55, , , ,Toyota RAV4, , , ,Sport Utility, , , ,17.148, , , ,55, , , ,Chevrolet S-10 Extended Cab, , , ,Small Pickup, , , ,18.847, , , ,46, , , ,Dodge Dakota Club Cab Sport, , , ,Small Pickup, , , ,16.870, , , ,53, , , ,Ford Ranger XLT Regular Cab, , , ,Small Pickup, , , ,18.510, , , ,48, , , ,Ford Ranger XLT Supercab, , , ,Small Pickup, , , ,20.225, , , ,55, , , ,GMC Sonoma Regular Cab, , , ,Small Pickup, , , ,16.938, , , ,44, , , ,Isuzu Hombre Spacecab, , , ,Small Pickup, , , ,18.820, , , ,41, , , ,Mazda B4000 SE Cab Plus, , , ,Small Pickup, , , ,23.050, , , ,51, , , ,Nissan Frontier XE Regular Cab, , , ,Small Pickup, , , ,12.110, , , ,51, , , ,Toyota Tacoma Xtracab, , , ,Small Pickup, , , ,18.228, , , ,49, , , ,Toyota Tacoma XtracabV6, , , ,Small Pickup, , , ,19.318, , , ,50, , , ,Chevrolet K2500, , , ,Full-Size Pickup, , , ,24.417, , , ,60, , , ,Chevrolet Silverado 2500 Ext, , , ,Full-Size Pickup, , , ,24.140, , , ,64, , , ,Dodge Ram 1500, , , ,Full-Size Pickup, , , ,17.460, , , ,54, , , ,Dodge Ram Quad Cab 2500, , , ,Full-Size Pickup, , , ,32.770, , , ,63, , , ,Dodge Ram Regular Cab 2500, , , ,Full-Size Pickup, , , ,23.140, , , ,59, , , ,Ford F150 XL, , , ,Full-Size Pickup, , , ,22.875, , , ,58, , , ,Ford F-350 Super Duty Crew Cab XL, , , ,Full-Size Pickup, , , ,34.295, , , ,64, , , ,GMC New Sierra 1500 Ext Cab, , , ,Full-Size Pickup, , , ,27.089, , , ,68, , , ,Toyota Tundra Access Cab Limited, , , ,Full-Size Pickup, , , ,25.605, , , ,53, , , ,Toyota Tundra Regular Cab, , , ,Full-Size Pickup, , , ,15.835, , , ,58, , , , Develop a regression model that attempts to explain resale value as a function of truck type (use sport utility as the base), and linear and quadratic terms for suggested retail price (full model)., ,Develop a second simpler model (reduced model) by eliminating the single least significant factor (independent variable)., ,Which of the two models appears to be able to better predict resale value? Why?, ,For both of the models, develop point estimates and 95% confidence intervals for a Small Pickup that has a suggested retail price of $17,500.,Comments and Hints:, ,Do all work in a single worksheet., ,Keep all prices in $1000. Keep this in mind when making predictions of point estimate., ,Specify output range of regression output for first model as J1. Shade the cell holding the P-value for factor to be eliminated., ,Specify the output range of regression output for second model as J25., ,Do all estimations in columns A through H beginning in row 34., ,
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