Practical Significance Ranking of Regressors and Exact t Density R package practicalSigni version 0.1.2 Consider a possibly nonlinear nonparametric regression with p regressors. We provide evaluations by 13 methods to rank regressors by their practical significance or importance using various methods, including machine learning tools. Comprehensive methods are as follows. m6=Generalized partial correlation coefficient or GPCC by Vinod (2021)<doi:10.1007/s10614-021-10190-x> and Vinod (2022)<https://www.mdpi.com/1911-8074/15/1/32>. m7= a generalization of psychologists' effect size incorporating nonlinearity and many variables. m8= local linear partial (dy/dxi) using the 'np' package for kernel regressions. m9= partial (dy/dxi) using the 'NNS' package. m10= importance measure using the 'NNS' boost function. m11= Shapley Value measure of importance (cooperative game theory). m12 and m13= two versions of the random forest algorithm. Taraldsen's exact density for sampling distribution of correlations added. Software Depends: R (>= 4.3.0), np (>= 0.60), generalCorr (>= 1.2), Imports: xtable (>= 1.8.4), ShapleyValue (>= 0.2.0), NNS (>= 0.9), randomForest (>= 4.7), hypergeo (>= 1.2.13), Suggests: R.rsp Hrishikesh Vinod <vinod@fordham.edu> Comprehensive R Archive Network (CRAN) Hrishikesh Vinod [aut, cre] GPL (>= 2) 2023-12-01 application/tgz https://CRAN.R-project.org/package=practicalSigni doi:10.32614/CRAN.package.practicalSigni