- The U.S. Department of Energy’s Fuel Economy Guide provides fuel efficiency data for cars and trucks. The following regression output was obtained for a sample of 45 cars. The variable of interest is highway miles per gallon (Hwy MPG). The independent variables used in the analysis are as follows:
The class of the vehicle: Compact, Midsize or Large. Midsize = 1 if the car is a midsize, 0 otherwise. Similarly, Large = 1 if it is a large car, 0 otherwise.
Displcement: The engine displacement (size) in liters
Premium: Equals 1 if premium fuel is used, 0 if regular fuel is used
Cylinders: Number of cylinders
Regression Statistics |
|
|
|
|
|
|
Multiple R |
0.90 |
|
|
|
|
|
R Square |
|
|
|
|
|
|
Adjusted R Square |
0.79 |
|
|
|
|
|
Standard Error |
1.78 |
|
|
|
|
|
Observations |
45 |
|
|
|
|
|
|
|
|
|
|
|
|
ANOVA |
|
|
|
|
|
|
|
df |
SS |
MS |
F |
Significance F |
|
Regression |
5 |
536.75 |
107.35 |
33.85 |
0.00 |
|
Residual |
39 |
123.70 |
3.17 |
|
|
|
Total |
44 |
660.44 |
|
|
|
|
|
|
|
|
|
|
|
|
Coefficients |
Standard Error |
t Stat |
P-value |
Lower 95% |
Upper 95% |
Intercept |
28.40 |
1.26 |
22.48 |
0.00 |
25.85 |
30.96 |
Displacement |
0.30 |
0.70 |
0.43 |
0.67 |
-1.12 |
1.71 |
Cylinders |
-0.94 |
0.39 |
-2.40 |
0.02 |
-1.74 |
-0.15 |
Midsize |
4.92 |
0.78 |
6.33 |
0.00 |
3.35 |
6.49 |
Large |
1.88 |
0.75 |
2.51 |
0.02 |
0.37 |
3.40 |
Premium |
-0.79 |
0.60 |
-1.33 |
0.19 |
-2.00 |
0.41 |
- Suppose that a compact car has a 2.0 liter engine with 4 cylinders and uses premium fuel. Calculated the expected fuel efficiency of the car.
- How would you interpret the coefficient of “Large”?
- Which independent variables are significant at the 5% level and why?
- Calculate the missing R2 and comment on the goodness of fit.
- What is the 95% confidence interval for the coefficient of Displacement?
Trending nowThis is a popular solution!
Step by stepSolved in 2 steps
- Consider a linear regression model that relates school expenditures and family background to student performance in Massachusetts using 224 school districts. The response variable is the mean score on the MCAS (Massachusetts Comprehensive Assessment System) exam given in May 1998 to 10th-graders. Four explanatory variables are used: (1) STR is the student-to-teacher ratio, (2) TSAL is the average teacher’s salary, (3) INC is the median household income, and (4) SGL is the percentage of single family households. The Excel Regression output for the sample regression equation is given below. (a) What proportion of the variation in MCAS score is explained by the explanatory variables? (b) At the 5% level, are the explanatory variables jointly significant in explaining MCAS score? Explain briefly. (c) At the 5% level, which variables are individually significant at predicting MCAS score? Explain briefly. (d) Suppose a second regression model (Model 2) was generated using only…arrow_forwardThe manager of the Bayville police department motor pool wants to develop a forecast model for annual maintenance on police cars, based on mileage in the past year and age of the cars. The following data have been collected for eight different cars: a. Using Excel, develop a multiple regression equation for these data. b. What is the coefficient of determination for this regression equation? c. Forecast the annual maintenance cost for a police car that is 5 years old and will be driven 10,000 miles in 1 year.arrow_forwardAn economist wants to determine whether there is a linear relationship between a country's gross domestic product (GDP) and carbon dioxide emissions. The data are shown in the table below. c. Compute and interpret the correlation coefficient. d. Compute and interpret the coefficient of determination. e. Test for the significance of the linear relationship. Use a 0.05 level of significance. State your conclusion. Hint: Your conclusion is either of the following. • There is a significant linear relationship between a country's gross domestic product (GDP) and carbon dioxide emissions. • There is no significant linear relationship between a country's gross domestic product (GDP) and carbon dioxide emissions. GDP 1.6 3.6 4.9 1.1 0.9 2.9 2.7 2.3 1.6 1.5 (trillion dollars) Carbon Dioxide Emissions 428.2 828.8 1214.2 444.6 264 415.3 571.8 454.9 358.7 573.5 (millions of metric tons)arrow_forward
- 9. Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The caloric content and the sodium content (in milligrams) for 6 beef hot dogs are shown in the table below. Calories, x Sodium, y 160 130 330 120 70 190 (a) x = 170 calories (c) x = 150 calories 180 (b) x = 80 calories 420 470 360 250 530 (d) x = 210 calories Find the regression equation. x+( (Round to three decimal places as needed.) y = Choose the correct graph below. OA. О В. OC. OD. 560- 560 560 560- 200 G 0IN T> 200 200 Calories Calories Calories Calories (a) Predict the value of y for x = 170. Choose the correct answer below. O A. 411.632 O B. 543.752 O C. 455.672 O D. not meaningful (b) Predict the value of y for x = 80. Choose the correct answer below. O A. 411.632 О В. 257.492 O C.…arrow_forwardSuppose you pulled info regarding the sex of the victim and offender for murders in the United States. The data look something like this: Sex of Vic. Sex of Off. F M F 124 421 M 1609 3725 Assume that the sex of the victim is the response variable. What is the relative risk of being killed by female offender for male victims?arrow_forwardAn analyst wanted to analyze the relationship between the speed of a car (x) measured in mph and its gas mileage (y). As an experiment a car is operated at several different speeds and for each speed the gas mileage is measured. These data are shown below. Speed 25 35 45 50 60 65 70 Gas Mileage 40 39 37 33 30 27 25 What is the dependent variable? What is the independent variable?arrow_forward
- Is there a relationship between the weight and price of a mountain bike? The following data set gives the weights and prices for ten mountain bikes. Let the expanatory variable x be the weight in pounds and the response variable y be the bike's price. Weight (LB) 32 33 29 29 34 37 28 30 34 30 Price ($) 980 350 430 710 930 160 590 530 180 1090 a. Construct a scatterplot. Interpret. b. Find the regression equation. Interpret the slope in context. Does the y-intercept have contextual meaning? c. You decide to purchase a mountain bike that weighs 33 pounds. What is the predicted price for the bike? a. Which scatterplot below correctly shows the data? A. 254001200xy A coordinate system has a horizontal x-axis labeled from 25 to 40 in increments of 1 and a vertical y-axis labeled from 0 to 1200 in increments of 50. A cluster of plotted points that form a line that falls from left to…arrow_forwardListed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $105 million. Use a significance level of a = 0.05. Budget ($)in Millions Gross ($) in Millions 41 23 114 75 78 47 120 64 10 59 127 22 12 150 2 0 127 18 111 65 113 112 102 94 64 98 211 41 22 288 57 Click the icon to view the critical values of the Pearson correlation coefficient r. ..... x. (Round to one decimal place as needed.) The regression equation is = + The best predicted gross for a movie with a $105 million budget is $ million. (Round to one decimal place as needed.)arrow_forwardThe following data on price ($) and the overall score for 6 stereo headphones that were tested by Consumer Reports were as follows. The estimated regression equation for these data is ŷ=27.654+0.29x. Brand Price Score Bose 180 76 Scullcandy 160 73 Koss 85 64 Phillips/O'Neill 70 57 Denon 80 50 JVC 45 26 a. Does the t test indicate a significant relationship between price and the overall score? Compute the value of the t test statistic. Use α=0.05 b. Show the ANOVA table for these data. Round your answers to three decimal places (and p-value to 4 decimal places), if necessary. Do not round intermediate calculations.arrow_forward
- MATLAB: An Introduction with ApplicationsStatisticsISBN:9781119256830Author:Amos GilatPublisher:John Wiley & Sons IncProbability and Statistics for Engineering and th...StatisticsISBN:9781305251809Author:Jay L. DevorePublisher:Cengage LearningStatistics for The Behavioral Sciences (MindTap C...StatisticsISBN:9781305504912Author:Frederick J Gravetter, Larry B. WallnauPublisher:Cengage Learning
- Elementary Statistics: Picturing the World (7th E...StatisticsISBN:9780134683416Author:Ron Larson, Betsy FarberPublisher:PEARSONThe Basic Practice of StatisticsStatisticsISBN:9781319042578Author:David S. Moore, William I. Notz, Michael A. FlignerPublisher:W. H. FreemanIntroduction to the Practice of StatisticsStatisticsISBN:9781319013387Author:David S. Moore, George P. McCabe, Bruce A. CraigPublisher:W. H. Freeman