At vero eos et accusamus et iusto odio dignissimos ducimus qui blanditiis praesentium voluptatum deleniti atque corrupti quos dolores et quas molestias excepturi sint occaecati cupiditate non provident, similique sunt in culpa qui officia deserunt mollitia animi, id est laborum et dolorum fuga. Et harum quidem rerum facilis est et expedita distinctio. Nam libero tempore, cum soluta nobis est eligendi optio cumque nihil impedit quo minus id quod maxime placeat facere possimus, omnis voluptas assumenda est, omnis dolor repellendus. Itaque earum rerum hic tenetur a sapiente delectus, ut aut reiciendis voluptatibus maiores alias consequatur aut perferendis doloribus asperiores repellat.
can you explain that?
its about statistics
yes let me see how I want to explain it
The second part is asking you for the value of R^2. Sounds familiar?
ow ` I just have to square it ?
what if it asks The Buick Regal has a horsepower of 127. What is the predicted mileage for the Buick Regal?
i have to plug 127 into function?
what about this one Predicting the value of a response variable for an individual whose x-value is out of our range of data is called
Then you can still use the regression line to derive an predicted value for y, given the x. However, it is likely to be less reliable for an x outside the range of x in the original sample, particularly if it is a long way outside of that range.
so how should I answer this question ?
I'm guessing just use your regression line if it asking you for an actual predicted y value
Im sorry, I dont get it
is it going to be extrapolation
I think it asking for definition of extrapolation
Well, that's why you have a textbook. Look it up.
so, my last question is What is the residual for the Chevy Malibu?
Residual is the difference between the predicted and actual value. So calculate the predicted value and compare it to the actual.
So, I have to plug 251 and 28 into fuction?
No. You are predicting one variable in terms of the other, using the regression line. You are predicting the value of y, given x. You are predicting the value of mileage as a function of horsepower. That gives you the predicted value of mileage. The residual is then the difference between this predicted number and the actual mileage. These are fundamental concepts. I recommend you go back and re-read your lecture notes and/or the chapter in your text book to make sure you have this straight.
ok , got it thanks
I got the answer for that -2.1380
could you expalin this one?
Suppose we had instead measured mileage in kilometers per liter (1 m/g = 0.425 km/l). What would be the value of the correlation between X and Y?
to change from mile per gallon to km per liter you would multiply each mileage value by a conversion factor (a fixed number). call that number a. If you plug in that factor everywhere into your formula how does it change the final correlation ?
is it 0.8651 ?
yes, it stays the same. But you can prove it to yourself.
but when I enter the answer 0.8651 . it says , it's wrong
now ,its right , thank you very much