according to HomeworkLib rules I have solved first 4 sub parts of the question
he follo 2. Do heavier cars really use more gasoline? Suppose that a car is chosen...
Do heavier cars really use more gasoline? Suppose a car is chosen at random. Let x be the weight of the car (in hundreds of pounds), and let y be the miles per gallon (mpg). x 30 43 31 47 23 40 34 52 y 30 21 22 13 29 17 21 14 Complete parts (a) through (e), given Σx = 300, Σy = 167, Σx2 = 11,908, Σy2 = 3761, Σxy = 5885, and r ≈ −0.888. (a) Draw...
Do heavier cars really use more gasoline? Suppose a car is chosen at random. Let x be the weight of the car (in hundreds of pounds), and let y be the miles per gallon (mpg). x 29 44 33 47 23 40 34 52 y 32 20 26 13 29 17 21 14 Complete parts (a) through (e), given Σx = 302, Σy = 172, Σx2 = 12,064, Σy2 = 4036, Σxy = 6066, and r ≈ −0.902. (a) Draw...
7. Do heavier cars really use more gasoline? Suppose a car is chosen at random. Let x be the weight of the car (in hundreds of pounds), and let y be the miles per gallon (mpg) At the 5% level of significance, test the claim is that heavier cars use more gasoline. Remember that a claim of correlation would be that X 29 46 29 47 23 40 34 52 Y 30 21 22 14 29 27 22 34 a....
5). a. An engineer wants to determine how the weight of a gas-powered car, x, affects gas mileage, y. The accompanying data represent the weights of various domestic cars and their miles per gallon in the city for the most recent model year. Complete parts (a) through (d) below. Click here to view the weight and gas mileage data. (a) Find the least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable. y...
Q6). We are interested in exploring the relationship between the weight of a vehicle and its fuel efficiency (gasoline mileage). The data in the table show the weights, in pounds, and fuel efficiency, measured in miles per gallon, for a sample of 12 vehicles. Weight Fuel Efficiency 2710 24 2550 24 2680 29 2720 38 3000 25 3410 22 3640 21 3700 27 3880 21 3900 19 4060 21 4710 16 Part (c) Find the equation of the best fit...
e7 Assignments 10.4 Homework Suppose a car is chosen at random. Let x be the weight of the car (in hundreds of pounds), and let y be the miles per gallon (mpg). Fill in the table below (last row is for sums) 43 39 41 39 52 51 (last row of table is for sums) Calculate the following by hand: Regression Equation Predict the miles per gallon of the car if the car weighs when 5,100 pounds. Points possible: 1
8. An engineer wanted to determine how the weight of a car (a) Determine which variable is the likely explanatory affects gas mileage. The following data represent the weight variable and which is the likely response variable. of various cars and their gas mileage. Complete parts (a) through (d). The explanatory variable is the miles Miles per per gallon and the response variable is Car Weight (pounds) Gallon the weight А 3310 19 The explanatory variable is the weight 3680...
An engineer wants to determine how the weight of a car, x, affects gas mileage, y. The following data represent the weights of various cars and their miles per gallon. Car 2555 2905 3400 3840 4095 26.1 20.6 18.9 13.7 11.5 Weight (pounds), x Miles per Gallon, y (a) Find the least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable Write the equation for the least-squares regression line y0.009x+ 48.108 (Round the...
The accompanying data represent the weights of various domestic cars and their gas mileages in the city. The linear correlation coefficient between the weight of a car and its miles per gallon in the city is r = −0.978. The least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable is ŷ=−0.0067x+43.2680. Car Weight (pounds), x Miles per Gallon, y 1 3,765 18 2 3,984 17 3 3,530 21 4 3,175 23 5 ...
The accompanying data represent the weights of various domestic cars and their gas mileages in the city. The linear correlation coefficient between the weight of a car and its miles per gallon in the city is r= -0.974. The least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable is y = -0.0066x + 43.3298. Complete parts (a) through (c) below. E:: Click the icon to view the data table. (a) What proportion...