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Overview

inferr builds upon the statistical tests provided in stats, provides additional and flexible input options and more detailed and structured test results. As of version 0.3, inferr includes a select set of parametric and non-parametric statistical tests which are listed below:

  • One Sample t Test
  • Paired Sample t Test
  • Independent Sample t Test
  • One Sample Proportion Test
  • Two Sample Proportion Test
  • One Sample Variance Test
  • Two Sample Variance Test
  • Binomial Test
  • ANOVA
  • Chi Square Goodness of Fit Test
  • Chi Square Independence Test
  • Levene’s Test
  • Cochran’s Q Test
  • McNemar Test
  • Runs Test for Randomness

Installation

# install inferr from CRAN
install.packages("inferr")

# the development version from github
# install.packages("devtools")
devtools::install_github("rsquaredacademy/inferr")

Shiny App

Use infer_launch_shiny_app() to explore the package using a shiny app.

Usage

One Sample t Test

infer_os_t_test(hsb, write, mu = 50, type = 'all')
#>                               One-Sample Statistics                               
#> ---------------------------------------------------------------------------------
#>  Variable    Obs     Mean     Std. Err.    Std. Dev.    [95% Conf. Interval] 
#> ---------------------------------------------------------------------------------
#>   write      200    52.775     0.6702       9.4786       51.4537    54.0969   
#> ---------------------------------------------------------------------------------
#> 
#>                                   Two Tail Test                                  
#>                                  ---------------                                  
#> 
#>                                Ho: mean(write) ~=50                              
#>                                Ha: mean(write) !=50                               
#> --------------------------------------------------------------------------------
#>  Variable      t      DF       Sig       Mean Diff.    [95% Conf. Interval] 
#> --------------------------------------------------------------------------------
#>   write      4.141    199    0.99997       2.775         1.4537     4.0969   
#> --------------------------------------------------------------------------------

ANOVA

infer_oneway_anova(hsb, write, prog)
#>                                 ANOVA                                  
#> ----------------------------------------------------------------------
#>                    Sum of                                             
#>                    Squares     DF     Mean Square      F        Sig.  
#> ----------------------------------------------------------------------
#> Between Groups    3175.698      2      1587.849      21.275    0.0000 
#> Within Groups     14703.177    197      74.635                        
#> Total             17878.875    199                                    
#> ----------------------------------------------------------------------
#> 
#>                  Report                   
#> -----------------------------------------
#> Category     N       Mean      Std. Dev. 
#> -----------------------------------------
#>    1        45      51.333       9.398   
#>    2        105     56.257       7.943   
#>    3        50      46.760       9.319   
#> -----------------------------------------
#> 
#> Number of obs = 200       R-squared     = 0.1776 
#> Root MSE      = 8.6392    Adj R-squared = 0.1693

Chi Square Test of Independence

infer_chisq_assoc_test(hsb, female, schtyp)
#>                Chi Square Statistics                 
#> 
#> Statistics                     DF    Value      Prob 
#> ----------------------------------------------------
#> Chi-Square                     1    0.0470    0.8284
#> Likelihood Ratio Chi-Square    1    0.0471    0.8282
#> Continuity Adj. Chi-Square     1    0.0005    0.9822
#> Mantel-Haenszel Chi-Square     1    0.0468    0.8287
#> Phi Coefficient                     0.0153          
#> Contingency Coefficient             0.0153          
#> Cramer's V                          0.0153          
#> ----------------------------------------------------

Levene’s Test

infer_levene_test(hsb, read, group_var = race)
#>            Summary Statistics             
#> Levels    Frequency    Mean     Std. Dev  
#> -----------------------------------------
#>   1          24        46.67      10.24   
#>   2          11        51.91      7.66    
#>   3          20        46.8       7.12    
#>   4          145       53.92      10.28   
#> -----------------------------------------
#> Total        200       52.23      10.25   
#> -----------------------------------------
#> 
#>                              Test Statistics                              
#> -------------------------------------------------------------------------
#> Statistic                            Num DF    Den DF         F    Pr > F 
#> -------------------------------------------------------------------------
#> Brown and Forsythe                        3       196      3.44    0.0179 
#> Levene                                    3       196    3.4792     0.017 
#> Brown and Forsythe (Trimmed Mean)         3       196    3.3936     0.019 
#> -------------------------------------------------------------------------

Cochran’s Q Test

infer_cochran_qtest(exam, exam1, exam2, exam3)
#>    Test Statistics     
#> ----------------------
#> N                   15 
#> Cochran's Q       4.75 
#> df                   2 
#> p value          0.093 
#> ----------------------

McNemar Test

hb <-
   hsb %>%
     mutate(
       himath = if_else(math > 60, 1, 0),
       hiread = if_else(read > 60, 1, 0)
     )
infer_mcnemar_test(hb, himath, hiread)
#>            Controls 
#> ---------------------------------
#> Cases       0       1       Total 
#> ---------------------------------
#>   0        135      21        156 
#>   1         18      26         44 
#> ---------------------------------
#> Total      153      47        200 
#> ---------------------------------
#> 
#>        McNemar's Test        
#> ----------------------------
#> McNemar's chi2        0.2308 
#> DF                         1 
#> Pr > chi2              0.631 
#> Exact Pr >= chi2      0.7493 
#> ----------------------------
#> 
#>        Kappa Coefficient         
#> --------------------------------
#> Kappa                     0.4454 
#> ASE                        0.075 
#> 95% Lower Conf Limit      0.2984 
#> 95% Upper Conf Limit      0.5923 
#> --------------------------------
#> 
#> Proportion With Factor 
#> ----------------------
#> cases             0.78 
#> controls         0.765 
#> ratio           1.0196 
#> odds ratio      1.1667 
#> ----------------------

Getting Help

If you encounter a bug, please file a minimal reproducible example using reprex on github. For questions and clarifications, use StackOverflow.

Code of Conduct

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.