Intro Stats, Books a la Carte Edition (5th Edition)
5th Edition
ISBN: 9780134210285
Author: Richard D. De Veaux, Paul Velleman, David E. Bock
Publisher: PEARSON
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Chapter R, Problem 2.19RE
a.
To determine
Explain whether the residua plot suggests that the conditions for regression satisfied.
b.
To determine
Explain whether the new model is more preferable than the one obtained in exercise R2.18.
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Before buying a new car , a consumer wants to learn how the weight of a car affects highway gas mileage. Statistical software was used to conduct a simple linear regression about the relationship between the weight (in lbs) of a car and its highway mpg. The following equation for the regression line was given:
mpg=49.5-0.0081weight
If your car weighs 3200 lbs , what does the model predict in the highway mpg? Round to 1 decimal places.
Using the attached information, answer the following:
1. Fill in the blank: For these data, mileages that are greater than the mean of the mileages tend to be paired with used selling prices that are _____ the mean of the used selling prices.
Choose one
greater than
less than
2. According to the regression equation, for an increase of one thousand miles in Cadet mileage, there is a corresponding decrease of how many thousand dollars in the used selling price?
3. What was the observed used selling price (in thousands of dollars) when the mileage was 37.7 thousand miles?
4. From the regression equation, what is the predicted used selling price (in thousands of dollars) when the mileage is 37.7 thousand miles? (Round your answer to at least one decimal place.)
The following multiple regression printout can be used to predict the price (Price) of a used car given how many miles it has on it (Mileage), the size of the engine (Liter), and whether it has leather interior (Leather), where Leather = 1 for cars that have leather interior and 0 otherwise.
%3D
Regression Analysis: Price Versus Mileage, Liter, Leather
Coefficients
Term
Coef
SE Coef
T-Value
P-Value
Constant
6,959
511
13.62
0.000
Mileage
-0.0848
0.0178
-4.76
0.000
Liter
3,795
126
30.12
0.000
Leather
1,028
311
3.31
0.001
Regression Equation
Price = 6,959 - 0.0848 Mileage + 3, 795 Liter + 1,028 Leather
(a) Given this Minitab printout, is the response variable in this multiple regression equation a categorical or a numerical variable?
O numerical
O categorical
(b) Determine whether the following statement is true or false.
Given this Minitab printout, the regression coefficient for miles on the car (Mileage) is statistically significant at a = 0.05.
O True
O False
(c) Determine whether the…
Chapter R Solutions
Intro Stats, Books a la Carte Edition (5th Edition)
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