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| Group: |
sci.stat.consult |
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| Author: |
Scott Seidman |
| Subject: |
Re: multiple linear regression |
| Body: |
wallisjon@gmail.com wrote in news:e279a357-ff1d-4c77-91ec-
30530031854f@p25g2000pri.googlegroups.com:
> Hi,
>
> I'm having trouble interpreting the results of a multiple linear
> regression, or at least matching it up to what I've obtained with
> other statistical tests. I have one dependent variable, and two
> independent variables. When I run the analysis through a 2-way ANOVA I
> get a highly significant main effect for IV1 (p<10-15) with no other
> main effect or interaction. When I run the data through a multiple
> linear regression (with IV1, IV2 and IV1*IV2), I get a significant F
> value for the overall regression equation (again p<10-15). However,
> when I look at significance of the individual regression coefficients
> (using a t-test) IV1 is a lot less significant (p<0.005), while IV2
> and the interaction are not significant. Why is there such a huge
> difference between the significance of the overall equation and the
> significance of the individual regression coeefficients? What am I
> missing here?
>
> Any help appreciated!
>
> Jon
Don't worry about "a lot less significant". Pick your alpha, and stick
with it.
--
Scott
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