dear R community,

I am running a linear regression for my dataset between 2 variables

(disk mass and velocities).

This is the result returned by the summary function onto the lm object

for one of my dataset.

Call:

lm(formula = df$md1 ~ df$logV, data = df)

Residuals:

Min 1Q Median 3Q Max

-0.64856 -0.16492 0.04127 0.18027 0.45727

Coefficients:

Estimate Std. Error t value Pr(>|t|)

(Intercept) 6.2582 0.2682 23.333 < 2e-16 ***

df$logV 1.2926 0.2253 5.738 6.5e-06 ***

---

Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.3067 on 24 degrees of freedom

Multiple R-squared: 0.5784, Adjusted R-squared: 0.5609

F-statistic: 32.93 on 1 and 24 DF, p-value: 6.504e-06

I am interested to give the significance in terms of sigmas (as

generally done in particle physics, see for instance the 7 \sigma

discovery of the Higgs particle)

of my regression.

For this, if I understood well, I should look at the p-value for the

F-statistic which is in this univariate linear regression the same as

the one for logV.

My question is, am I right if I state that the significance in terms of

sigmas (sign) is given by: p = 2*(1-pnorm(sign)) since I guess the

p-value returned by R is for a two sided test (and assuming Gaussianity

for my dataset)?

Otherwise is there any way to get the significance of this linear

regression in terms of sigmas?

I would have a similar question also, as extension, for a multivariate

linear regression for which the p-value associated to F statistics is

not the same as the p-value for each variable of the regression.

Thanks in advance,

Best Regards

Jean-Philippe Fontaine

--

Jean-Philippe Fontaine

PhD Student in Astroparticle Physics,

Gran Sasso Science Institute (GSSI),

Viale Francesco Crispi 7,

67100 L'Aquila, Italy

Mobile: +393487128593, +33615653774

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