Sorry to say so, but you seem confused. The "sigma" in physics parlance is presumably the s.e. of the estimate so the "number of sigmas" equal the t statistic, in this case 5.738. However, use of that measure ignores the t distribution, effectively assuming that there are infinite df (and 24 in not quite infinite).
- pd > On 20 Jun 2018, at 12:53 , jean-philippe <jeanphilippe.fonta...@gssi.infn.it> > wrote: > > 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 > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. -- Peter Dalgaard, Professor, Center for Statistics, Copenhagen Business School Solbjerg Plads 3, 2000 Frederiksberg, Denmark Phone: (+45)38153501 Office: A 4.23 Email: pd....@cbs.dk Priv: pda...@gmail.com ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
