Chapter 12, Problem 12.4AC

Suppose you a manager for a local car dealership, and you want to use a linear regression model to predict the price of a used car. You decide to use four predictor variables - "Age' (how long the car has been in use since it was produced), "Dents" (the number of visible dents on the outside of the car), "Accidents" (the number of accidents the car has been in), and "mpg" (the fuel efficiency of the car, measured in miles per gallon). Your dataset contains this information for the past 120 cars sold at your dealership. Using this model, your analysis finds an R² of 37%. What is the F statistic of your analysis? Note: 1- Only round your final answer. Round your final answer to two decimal places.

Consumers are often interested in the fuel efficiency of the vehicles they choose to buy, so much so that they will research the various models they consider buying. Fuel efficiency can depend on a variety of variables. In this analysis, there are 73 automobiles that are popular with consumers. A regression analysis has been performed; the dependent variable is CityMPG (EPA miles per gallon in city driving), and independent variables are Length (vehicle length in inches), Width (vehicle width in inches), Weight (vehicle weight in pounds), and ManTran (1 if manual shift transmission, 0 otherwise). The level of significance is 0.05. Use the following MegaStat output to answer questions about this regression analysis. a. State the regression equation. b. How would CityMPG be affected if the width of a vehicle increased by an inch? c. Estimate the CityMPG for a vehicle with a length of 190 inches, a width of 75 inches, a weight of 4100 pounds, and a manual. Round your answer to the nearest…

Consumer Reports tested 19 different brands and models of road, fitness, and comfort bikes. Road bikes are designed for long road trips; fitness bikes are designed for regular workouts or daily commuters; and comfort bikes are designed for leisure rides on typically flat roads. The data file Bikes show the type, weight (lb.), and price ($) for the 20 bicycles tested. Develop an estimated regression equation that can be used to predict Price by using Type and Weight. Brand and Model Type Weight Price Klein Rêve v Road 20 1800 Giant OCR Composite 3 Road 22 1800 Giant OCR 1 Road 22 1000 Specialized Roubaix Road 21 1300 Trek Pilot 2.1 Road 21 1320 Cannondale Synapse 4 Road 21 1050 LeMond Poprad Road 22 1350 Raleigh Cadent 1.0 Road 24 650 Giant FCR3 Fitness 23 630 Schwinn Super Sport GS Fitness 23 700 Fuji Absolute 2.0 Fitness 24 700 Jamis Coda Comp Fitness 26 830 Cannondale Road Warrior 400 Fitness 25 700 Schwinn Sierra GS Comfort 31 340 Mongoose…

The general manager of an engineering firm wants to know whether a technical artist's experience influences the quality of his or her work. A random sample of 24 artists is selected and their years of work experience and quality rating (as assessed by their supervisors) recorded. Work experience (EXPER) is measured in years and quality rating (RATING) takes a value of 1 through 7, with 7 = excellent and 1 = poor. The simple regression model RATING = ẞ1 + ẞ₂EXPER+ € is proposed. The least squares estimates of the model, and the standard errors of the estimates, are RATING= 3.204 +0.076EXPER (se) (0.709) (0.044) (a) Interpret the coefficient of EXPER. (b) Construct a 95% confidence interval for B2, the slope of the relationship between quality rating and experience. In what are you 95% confident? (c) Test the null hypothesis that ẞ2 is zero against the alternative that it is not using a two-tail test and the α = 0.05 level of significance. What do you conclude? (d) Test the null…

A major brokerage company has an office in Miami, Florida. The manager of the office is evaluated based on the number of new clients generated each quarter. Data were collected that show the number of new customers added during each quarter between 2015 and 2018. A multiple regression model was developed with the number of new customers as the dependent and the following four independent variables: Period (1, …, 16): A variable that measures the trend; Q1 = 1 for first quarter, Q1 = 0 otherwise; Q2 = 1 for second quarter, Q2 = 0 otherwise; Q3 = 1 for third quarter, Q3 = 0 otherwise. Questions:   1. Explain each of the four slopes (Period, Q1, Q2, Q3).   2. How many new customers would you expect in the second quarter of the following year (2019)?

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Is the number of calories in a beer related to the number of carbohydrates​ and/or the percentage of alcohol in the​ beer? The accompanying table has data for 35 beers. The values for three variables are​ included: the number of calories per 12​ounces, the alcohol​ percentage, and the number of carbohydrates​ (in grams) per 12 ounces. a.  Perform a multiple linear regression​ analysis, using calories as the dependent variable and percentage alcohol and number of carbohydrates as the independent variables.   Let X1 represent alcohol percentage and let X2 represent the number of carbohydrates. ​(Round to four decimal places as​ needed.)

Assume we have data demonstrating a strong linear link between the amount of fertilizer applied to certain plants and their yield. Which is the independent variable in this research question?

In mammals, the toxicity of drugs, pesticides and chemical carcinogens can be altered by inducing liver enzyme activity. In a study on chickens, five liver enzymes had their activity induced by butylated hydroxytoluene, and the resulting percent detoxification of malathion (an organophosphate insecticide) was recorded. The experimenters believed that the response (% detoxification, DT) could be modelled by a multiple linear regression based on the activities of the individual enzymes (EAi, i = 1 to 5, measured as a percentage of normal activity): DT = b0 + b1×EA1 + b2×EA2 + b3×EA3 + b4×EA4 +b5×EA5                                            The results from the experiment are contained in the screenshot, which contains six variables: Detox – DT, the % detoxification of malathion by liver. EA1 – EA1, activity of enzyme 1 (% of normal activity). EA2 – EA2, activity of enzyme 2 (% of normal activity). EA3 – EA3, activity of enzyme 3 (% of normal activity). EA4 – EA4, activity of enzyme 4…