Question

Choose all that apply when describing R2. (Select all that apply.)

Can be inflated by removing variables.
Is used to determine the fit if a model.
Only describes the relationship between quantitative variables.
Is the correlation coefficient r2 in simple linear regression.
Is only used in multple linear regression.
Can be inflated by adding more variables.

Answer 1

@mathmale

Answer 2

I know it's not a or b

Answer 3

Please get started by choosing the likeliest answers and elim. the least likely answers (as you have just done).

Answer 4

I'd agree we toss out A.
I'll let you argue for your elimination of B.
But let's focus on finding the likeliest answers first.

Answer 5

okay so i know it's b

Answer 6

I just found that in my lecture notes.

Answer 7

e is another answer as well

Answer 8

okay I think it's b,d and e

Answer 9

inflated means if we were to add more predictors R^2 would go up?

Answer 10

Explain your choice of (d).
The correl. coeff. is simply r.

The quantity r^2 has a different name and different meaning. What are they?

Answer 11

hold on i am researching.

Answer 12

I apologize; I just realized that that "R2" appears in the main body of the question.

R2 is called the "coefficient of d......... " Can you complete this sentence?

Answer 13

coefficient of multiple determination

Answer 14

In statistics, the coefficient of determination, denoted R2 or r2 and pronounced R squared, is a number that indicates how well data fit a statistical model – sometimes simply a line or a curve

Answer 15

^the last statement is from wiki

Answer 16

That's quite good, and I appreciate your having looked that u p.

Yes, R2 is the "coefficient of determination."

We have to go back to the drawing board now and determine which of the several descriptors best apply to R2.

Mind starting out?

Answer 17

last part applies as well. I found it in my lecture notes. I got to go to class, but I think I need to do a little more research on R^2 because I have an understand of what it is, but not sure what exactly effects it. I may ask my instructor after class to explain to me. I will return later with an aswer.

Answer 18

OK. The Coeff. of Det. is often interpreted as "an indication of how well the regression line represents how the independent variable, x, determines the dependent variable, y."

If R=1, then R2=1, equivalent to 100%; that wuold say that the ind. var. would be pretty much the only predictor of y. This rarely happens, however.

Answer 19

Okay I got it figured out after discussing it with my instructor.