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Parametric and non-parametric statistical tests

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# inferr

Tools for Statistical Inference

## 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")```

## 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    0.00005       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
#> 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
hb\$himath <- ifelse(hsb\$math > 60, 1, 0)
hb\$hiread <- ifelse(hsb\$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.

## About

Parametric and non-parametric statistical tests

## Releases 4

inferr 0.3.1 Latest
May 29, 2021

## Packages 0

No packages published