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STATISTICS F/BUSINESS+ECONOMICS-TEXT
13th Edition
ISBN: 9781305881884
Author: Anderson
Publisher: CENGAGE L
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Textbook Question
Chapter 16, Problem 30SE
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 commutes; and comfort bikes are designed for leisure rides on typically flat roads. The following data show the type, weight (lb.), and price ($) for the 19 bicycles tested (Consumer Reports website, February 2009).
Brand and Model | Type | Weight | Price($) |
Klein RÃave 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 Switchback SX | Comfort | 32 | 280 |
Giant Sedona DX | Comfort | 32 | 360 |
Jamis Explorer 4.0 | Comfort | 35 | 600 |
Diamondback Wildwood Deluxe | Comfort | 34 | 350 |
Specialized Crossroads Sport | Comfort | 31 | 330 |
- a. Develop a
scatter diagram with weight as the independent variable and price as the dependent variable. Does a simple linear regression model appear to be appropriate? - b. Develop an estimated multiple regression equation with x = weight and x2 as the two independent variables.
- 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).
- 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 part (c). What estimated regression equation appears to be the best predictor of price? Explain.
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Examine the Variables: Carefully review and note the names of all variables in the dataset. Examples of these variables include:
Mileage (mpg)
Number of Cylinders (cyl)
Displacement (disp)
Horsepower (hp)
Research: Google to understand these variables.
Statistical Analysis: Select mpg variable, and perform the following statistical tests. Once you are done with these tests using mpg variable, repeat the same with hp
Mean
Median
First Quartile (Q1)
Second Quartile (Q2)
Third Quartile (Q3)
Fourth Quartile (Q4)
10th Percentile
70th Percentile
Skewness
Kurtosis
Document Your Results:
In RStudio: Before running each statistical test, provide a heading in the format shown at the bottom. “# Mean of mileage – Your name’s command”
In Microsoft Word: Once you've completed all tests, take a screenshot of your results in RStudio and paste it into a Microsoft Word document. Make sure that snapshots are very clear. You will need multiple snapshots. Also transfer these results to the…
Examine the Variables: Carefully review and note the names of all variables in the dataset. Examples of these variables include:
Mileage (mpg)
Number of Cylinders (cyl)
Displacement (disp)
Horsepower (hp)
Research: Google to understand these variables.
Statistical Analysis: Select mpg variable, and perform the following statistical tests. Once you are done with these tests using mpg variable, repeat the same with hp
Mean
Median
First Quartile (Q1)
Second Quartile (Q2)
Third Quartile (Q3)
Fourth Quartile (Q4)
10th Percentile
70th Percentile
Skewness
Kurtosis
Document Your Results:
In RStudio: Before running each statistical test, provide a heading in the format shown at the bottom. “# Mean of mileage – Your name’s command”
In Microsoft Word: Once you've completed all tests, take a screenshot of your results in RStudio and paste it into a Microsoft Word document. Make sure that snapshots are very clear. You will need multiple snapshots. Also transfer these results to the…
Chapter 16 Solutions
STATISTICS F/BUSINESS+ECONOMICS-TEXT
Ch. 16.1 - Consider the following data for two variables, x...Ch. 16.1 - Consider the following data for two variables, x...Ch. 16.1 - Prob. 3ECh. 16.1 - A highway department is studying the relationship...Ch. 16.1 - In working further with the problem of exercise 4,...Ch. 16.1 - A study of emergency service facilities...Ch. 16.1 - In 2011, home prices and mortgage rates fell so...Ch. 16.1 - Corvette, Ferrari, and Jaguar produced a variety...Ch. 16.1 - Kiplingers Personal Finance Magazine rated 359...Ch. 16.2 - In a regression analysis involving 27...
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Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.Similar questions
- Examine the Variables: Carefully review and note the names of all variables in the dataset. Examples of these variables include: Mileage (mpg) Number of Cylinders (cyl) Displacement (disp) Horsepower (hp) Research: Google to understand these variables. Statistical Analysis: Select mpg variable, and perform the following statistical tests. Once you are done with these tests using mpg variable, repeat the same with hp Mean Median First Quartile (Q1) Second Quartile (Q2) Third Quartile (Q3) Fourth Quartile (Q4) 10th Percentile 70th Percentile Skewness Kurtosis Document Your Results: In RStudio: Before running each statistical test, provide a heading in the format shown at the bottom. “# Mean of mileage – Your name’s command” In Microsoft Word: Once you've completed all tests, take a screenshot of your results in RStudio and paste it into a Microsoft Word document. Make sure that snapshots are very clear. You will need multiple snapshots. Also transfer these results to the…arrow_forward2 (VaR and ES) Suppose X1 are independent. Prove that ~ Unif[-0.5, 0.5] and X2 VaRa (X1X2) < VaRa(X1) + VaRa (X2). ~ Unif[-0.5, 0.5]arrow_forward8 (Correlation and Diversification) Assume we have two stocks, A and B, show that a particular combination of the two stocks produce a risk-free portfolio when the correlation between the return of A and B is -1.arrow_forward
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