# [R] How to interpret lm's coefficients?

PIKAL Petr petr.pikal at precheza.cz
Thu Sep 8 16:25:41 CEST 2016

```Hi

see in line

> -----Original Message-----
> From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Matti
> Viljamaa
> Sent: Thursday, September 8, 2016 2:44 PM
> To: r-help at R-project.org
> Subject: [R] How to interpret lm's coefficients?
>
> I’m trying to understand how to interpret the return values, specifically
> “Coefficients:”, of R’s lm function. I’m using it with a dichotomic predictor
> (mom_hs).
>
> lm(data\$kid_score ~ data\$mom_hs) returns
>
> Coefficients:
> #   (Intercept)  data\$mom_hs
> # 77.55        11.77
>
> I read that the (Intercept) value is the “y-intercept” value b, i.e. the y value
> where the line intercept the y-axis.
>
> The second value is the value of the term m (or “slope”) in the equation of a
> line y=mx+b.
>
> However,
>
> These two numbers also have the following interpretations:
>
> b or (Intercept) value is the same as:
> The mean of those data\$kid_score that have data\$mom_hs == 0.
> Why is this a valid interpretation?

Well, you should rather to look into some statistical textbook. E.g.
Practical Regression and Anova using R,  Julian J. Faraway
or
SimpleR, J. Verzani

The explanation is not for few lines of plain text short mail.

But maybe others will disagree.

Cheers
Petr

PS.
Or you can try to find an interpretation from plots yourself.

plot(data\$kid_score ~ data\$mom_hs)
abline( lm(data\$kid_score ~ data\$mom_hs)

>
> m or data\$mom_hs value is the same as:
> The difference of means between those data\$kid_score that have
> data\$mom_hs == 1 and those data\$kid_score that have data\$mom_hs == 0.
> Why is this a valid interpretation?
>
> Can someone explain?
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> guide.html
> and provide commented, minimal, self-contained, reproducible code.

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