Nathasha Karp has written a detailed introduction to R Commanderįor more detailed installation and configuration instructions, click here. After you have installed R Commander, this is also available from the Help button under “Introduction to the R Commander.” He has written a piece on getting started with R Commander available This is a very nice way to learn R and introduce yourself to the command language.
This interface generates R commands using a pull-down menu scheme. R Commander – a graphical user interface (GUI).Certainly, many, many analysts developed their R skills in the early days on this interface. For some users, it can be nice to interact more directly with the core engine.
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Var 27.839 #> Pred R-Squared 0.700 AIC 730.620 #> MAE 137.656 SBC 744.543 #> - #> RMSE: Root Mean Square Error #> MSE: Mean Square Error #> MAE: Mean Absolute Error #> AIC: Akaike Information Criteria #> SBC: Schwarz Bayesian Criteria #> #> ANOVA #> - #> Sum of #> Squares DF Mean Square F Sig. The linear regression version of the program runs on both Macs and PC's, and there is also a separate logistic regression version for the PC with highly interactive table and chart output. # stepwise aic backward regression model #> #> Stepwise Summary #> - #> Step Variable AIC SBC SBIC R2 Adj.
Var 27.839 #> Pred R-Squared 0.700 AIC 730.620 #> MAE 137.656 SBC 744.543 #> - #> RMSE: Root Mean Square Error #> MSE: Mean Square Error #> MAE: Mean Absolute Error #> AIC: Akaike Information Criteria #> SBC: Schwarz Bayesian Criteria #> #> ANOVA #> - #> Sum of #> Squares DF Mean Square F Sig.
# stepwise regression model #> #> Stepwise Summary #> - #> Step Variable AIC SBC SBIC R2 Adj.
Var 13.051 #> Pred R-Squared 0.771 AIC 159.070 #> MAE 1.858 SBC 167.864 #> - #> RMSE: Root Mean Square Error #> MSE: Mean Square Error #> MAE: Mean Absolute Error #> AIC: Akaike Information Criteria #> SBC: Schwarz Bayesian Criteria #> #> ANOVA #> - #> Sum of #> Squares DF Mean Square F Sig. Ols_regress ( mpg ~ disp + hp + wt + qsec, data = mtcars ) #> Model Summary #> - #> R 0.914 RMSE 2.409 #> R-Squared 0.835 MSE 6.875 #> Adj.
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