On 20/06/2018 6:53 AM, jean-philippe 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.
The t value is probably what you want, but I think you'll have to ask your supervisor for the definition used in your area.
Duncan Murdoch
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
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