Patrick Cronin
5/8/2016
This web interface allows users to run linear regression on the R mtcars data set and has the following advantages
The code looks scary if you can't code
data("mtcars")
modelFit = lm(mpg ~ cyl + disp+ wt,data = mtcars)
summary(modelFit)
Novices may react
Call:
lm(formula = mpg ~ cyl + disp + wt, data = mtcars)
Residuals:
Min 1Q Median 3Q Max
-4.4035 -1.4028 -0.4955 1.3387 6.0722
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 41.107678 2.842426 14.462 1.62e-14 ***
cyl -1.784944 0.607110 -2.940 0.00651 **
disp 0.007473 0.011845 0.631 0.53322
wt -3.635677 1.040138 -3.495 0.00160 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 2.595 on 28 degrees of freedom
Multiple R-squared: 0.8326, Adjusted R-squared: 0.8147
F-statistic: 46.42 on 3 and 28 DF, p-value: 5.399e-11