# Regression Model Analysis

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- This topic has 5 replies, 4 voices, and was last updated 14 years, 7 months ago by McMurray.

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- January 27, 2006 at 6:40 am #42166
Can someone help me with the following:1-What is T Test, what does is measure and when is it considered good or bad? (Significant)2-What is F Test, what does is measure and when is it considered good or bad?3-What is R Square, what does is measure and when is it considered good or bad.4-What is Adjusted R Square, what does is measure and when is it considered good or bad.5-What is P-Value, what does is measure and when is it considered good or bad.6-What is standared Deviation, what does is measure and when is it considered good or bad.

0January 27, 2006 at 3:52 pm #1329881. t-test – measures difference between two means

2. F-test – measures the difference between two standard deviations

3. R2 – is a crude summary of the variance observed in the data that is explained by terms in a model.

4. Adjusted R2 – same as 3 only modified to take into account model parameters.

5. P value is a measure of significance

6. Standard deviation is a measure of the scatter of the data about a mean.

As for good or bad – it depends on what you are doing and the kind of data you have – there are a bunch of rules of thumb but each one has a list of “yeah-but’s” a mile long. I’d recommend you check you class notes to determine what your teacher considers to be “good or bad”.0January 27, 2006 at 4:15 pm #132989Bob, significant mean that a test have been done and it produced a result ‘p’ < of 'x'.

It is called significant for p<0,05 ; Very significat for p< 0,01 ; highly significant for p<0,001

Rgs, Peppe0January 28, 2006 at 3:47 am #133028Thanks guys for the help

0January 28, 2006 at 4:04 am #133029Thanks guys for the help

0February 1, 2006 at 4:26 am #133184The F-test measures the difference between 2 variances. R^2 is the coefficient of determination and tells you how much of the response is explained by the variables in your regression model. R2-adj accounts for the DOF, not your model parameters.

And there are no degrees of significance, a statistical parameter is either significant or not based on the level of significance chosen for the test.

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