SAS Exam A00-240 Topic 9 Question 91 Discussion

Actual exam question for SAS's A00-240 exam

Question #: 91
Topic #: 9

[All A00-240 Questions]

Refer to the REG procedure output:

Calculate the coefficient of determination, R-Square.

Enter your numeric answer in the space below. Round to 4 decimal places (example: n.nnnn).

A0.5671

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Suggested Answer: A

by Johnson at Jul 05, 2024, 12:23 AM

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Skye

22 days ago

R-Square, huh? I always thought it was called the 'Regression Coefficient of Determination'. Guess I've been living in a parallel universe this whole time. 0.5671? Sounds good to me - as long as it's not 0.5670, that's just bad luck!

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Leota

1 days ago

I agree, R-Square is another name for the coefficient of determination. And yes, 0.5671 is the correct value.

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Cyril

28 days ago

Ah, the good old R-Square. The bane of every statistician's existence, but also their most prized possession. 0.5671, huh? Sounds like a pretty solid answer to me. Time to move on to the next question and pray I don't have to do any more math.

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Stephaine

9 days ago

I agree, R-Square can be a tricky one to calculate.

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Theodora

1 months ago

Ugh, regression analysis... not my favorite topic. But I guess I better buckle down and figure this out. 0.5671, you say? Alright, let's plug that into the equation and see if it checks out.

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Maile

1 months ago

R-Square, huh? I remember learning about that in my statistics class. It's a pretty important metric for evaluating the goodness of fit of a regression model. 0.5671 seems like a reasonable answer, but I better verify it against the formula just to be sure.

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Cherelle

So, did you calculate the R-Square for this particular regression model?

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Armanda

23 days ago

Yeah, it measures the proportion of the variance in the dependent variable that is predictable from the independent variable.

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Nidia

1 months ago

I think you're right, R-Square is definitely important for regression models.

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Wendell

1 months ago

Okay, let's see... The R-Square value is the coefficient of determination, which measures the proportion of the variance in the dependent variable that is predictable from the independent variable(s). Hmm, I think 0.5671 looks about right. Let me double-check my work.

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