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Consumer Reports tested 19 different brands and models of road, fitness, and comfort bikes. ligned for long road trips; fitness data show the type, weight

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Consumer Reports tested 19 different brands and models of road, fitness, and comfort bikes. ligned for long road trips; fitness data show the type, weight (1b.), and price ($) for the 19 bicycles tested. Click on the datafile logo to reference the data. DATA file Brand and Model TYPE weight Klein Reve V Price 20 Giant OCR Composite 3 Road 22 1800 Glant OCR 1 Road 22 1000 Spedalized Roubalx Road 21 DOET Trek Pilot 2.1 Road 21 OZET Cannondale Synapse 4 Road 21 1050 LeMond Poprad Road 22 OSET Raleigh Cadent 1.0 Road 650 Glant FOR3 Fitness 630 Schwinn Super Sport GS Fitness 700 Full Absolute 2.0 Fitness Jamis Coda Comp Fitness 830 Cannondale Road Warrior 400 Fitness Schwinn Sierra GS Comfort Mongoose Switchback 5X Comfort Giant Sedona DX Comfort Jamis Explorer 4.0 Comfort Diamondback Wildwood Deluxe Comfort Specialized Crossroads Sport Comfort a. Select a dent variable. Price ($) 1800 160D 140D 1200 1000 600- 400- 200- . .. 25 35 Weight ( 1b. ) Price ($) 160D 1400 1200 100D 800- 600-- 400 200- 25 30 35 Weight (Ib. ) Price ($) 160D 1 40D 1200 1000 800- . : . 400 200- 20 30 35 Weight (Ib. ) Price ($) 1800 - 160D -140D 1200 1000 800 600-- 400 200-- . . Weight (Ib. ) Select the correct scatter diagram from the options above. VIX Does a simple linear regression model ar to be appropriate? A simple linear regression model does not appear to be appropriate. Round your answ b. Develop an estimated multiple regression equation with a = Weight and z" = WeightSq as the two Independent variables. Weight + WeightSq c. Use the following dummy variables to develop an estimated regression equation that can be used to predict the price given the type of bike: Type_Fitness = 1 if the bike is a fitness bike, 0 otherwise; and Type_Comfort = 1 If the bike is a comfort bike; 0 otherwise. Compare the results obtained to the results obtained In part (b) Type_Fitness - Type_Comfort Type of bike appears to be a(n) significant factor in predicting developed in part (b) appears to provide a slightly better Vint. d. To account for possible Interaction between the type of bike and the weight of the bike, develop a new estimated regression equation that can be used to predict the price of the bike given the type, the weight of the bike, and any Interaction between weight and each of the dummy variables defined In art (c). What estimated regression equation appears to be the best predictor of price? Please round to four decimal places. Weight - Type_Fitness - Type_Comfort + WIF + WIC Hide Feedback Partially Correct

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