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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 = -0.971. The? least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable is Y with caret = -0.0064x + 42.6554.
Car Weight (pounds) X Miles per Gallon Y
1 3,765 19
2 3,984 18
3 3,530 20
4 3,175 22
5 2,580 26
6 3,730 18
7 2,605 25
8 3,772 18
9 3,310 21
10 2,991 25
11 2,752 26
The proportion of the variability in miles per gallon explained by the relation between weight of the car and miles per gallon is ____???? (round to one decimal if needed)
Construct a residual plot to verify the requirements of the? least-squares regression model.
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The purpose of including this question is to prove to you that a person can have an absolute advantage in producing some good without necessarily.
Describe what you should expect if you randomly select stocks and add them to your portfolio?
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