# lsr

**lsr** is a companion package to the textbook [*Learning Statistics
with R*](https://learningstatisticswithr.com). It provides
beginner-friendly wrappers for common statistical procedures — t-tests,
chi-square tests, effect sizes, correlation matrices, and basic data
manipulation — with output designed to be readable by students
encountering statistics for the first time.

## Example

Here is an independent-samples t-test comparing extra sleep between two
drug groups in the built-in `sleep` dataset:

``` r

library(lsr)
independentSamplesTTest(formula = extra ~ group, data = sleep)
#> 
#>    Welch's independent samples t-test 
#> 
#> Outcome variable:   extra 
#> Grouping variable:  group 
#> 
#> Descriptive statistics: 
#>                 1     2
#>    mean     0.750 2.330
#>    std dev. 1.789 2.002
#> 
#> Hypotheses: 
#>    null:        population means equal for both groups
#>    alternative: different population means in each group
#> 
#> Test results: 
#>    t-statistic:  -1.861 
#>    degrees of freedom:  17.776 
#>    p-value:  0.079 
#> 
#> Other information: 
#>    two-sided 95% confidence interval:  [-3.365, 0.205] 
#>    estimated effect size (Cohen's d):  0.832
```

Compared to base R’s [`t.test()`](https://rdrr.io/r/stats/t.test.html),
the output labels every component in plain English and automatically
reports Cohen’s *d* alongside the test result.

## Where to go next

- [**Guided
  overview**](https://lsr.djnavarro.net/articles/overview.html) — a
  hands-on introduction for students and beginners, working through
  descriptive statistics, reshaping data, and hypothesis testing with a
  single example dataset.
- [**Critical
  commentary**](https://lsr.djnavarro.net/articles/commentary.html) — an
  honest account of the package’s limitations and pointers to better
  tools for users who have outgrown it.
- [**Reference**](https://lsr.djnavarro.net/reference/) — documentation
  for all 29 functions, organised by topic.

## Installation

Install the released version from [CRAN](https://CRAN.R-project.org):

``` r

install.packages("lsr")
```

Or the development version from GitHub:

``` r

# install.packages("devtools")
devtools::install_github("djnavarro/lsr")
```

# Package index

## Hypothesis tests

Wrapper functions for common statistical tests used in introductory
courses, with output designed to be readable by beginners.

- [`oneSampleTTest()`](https://lsr.djnavarro.net/reference/oneSampleTTest.md)
  : One sample t-test
- [`independentSamplesTTest()`](https://lsr.djnavarro.net/reference/independentSamplesTTest.md)
  : Independent samples t-test
- [`pairedSamplesTTest()`](https://lsr.djnavarro.net/reference/pairedSamplesTTest.md)
  : Paired samples t-test
- [`associationTest()`](https://lsr.djnavarro.net/reference/associationTest.md)
  : Chi-square test of association / independence
- [`goodnessOfFitTest()`](https://lsr.djnavarro.net/reference/goodnessOfFitTest.md)
  : Chi-square goodness of fit test
- [`posthocPairwiseT()`](https://lsr.djnavarro.net/reference/posthocPairwiseT.md)
  : Post-hoc pairwise t-tests for ANOVA
- [`print(`*`<TTest>`*`)`](https://lsr.djnavarro.net/reference/print.TTest.md)
  : Print t-test results
- [`print(`*`<assocTest>`*`)`](https://lsr.djnavarro.net/reference/print.assocTest.md)
  : Print chi-square association test results
- [`print(`*`<gofTest>`*`)`](https://lsr.djnavarro.net/reference/print.gofTest.md)
  : Print goodness of fit test results

## Effect sizes and descriptive statistics

Functions for computing effect sizes and summarising data, intended as
companions to the hypothesis test functions above.

- [`cohensD()`](https://lsr.djnavarro.net/reference/cohensD.md) :
  Cohen's d
- [`etaSquared()`](https://lsr.djnavarro.net/reference/etaSquared.md) :
  Effect size for ANOVAs
- [`cramersV()`](https://lsr.djnavarro.net/reference/cramersV.md) :
  Cramer's V
- [`ciMean()`](https://lsr.djnavarro.net/reference/ciMean.md) :
  Confidence interval around the mean
- [`correlate()`](https://lsr.djnavarro.net/reference/correlate.md) :
  Correlation matrices
- [`print(`*`<correlate>`*`)`](https://lsr.djnavarro.net/reference/print.correlate.md)
  : Print correlation matrix results

## Data manipulation

Functions for reshaping, reordering, and recoding data frames and
factors.

- [`wideToLong()`](https://lsr.djnavarro.net/reference/wideToLong.md) :
  Reshape from wide to long
- [`longToWide()`](https://lsr.djnavarro.net/reference/longToWide.md) :
  Reshape from long to wide
- [`expandFactors()`](https://lsr.djnavarro.net/reference/expandFactors.md)
  : Expand factors to a set of contrasts
- [`permuteLevels()`](https://lsr.djnavarro.net/reference/permuteLevels.md)
  : Permute the levels of a factor
- [`quantileCut()`](https://lsr.djnavarro.net/reference/quantileCut.md)
  : Cut by quantiles
- [`sortFrame()`](https://lsr.djnavarro.net/reference/sortFrame.md) :
  Sort a data frame
- [`tFrame()`](https://lsr.djnavarro.net/reference/tFrame.md) :
  Transpose a data frame
- [`colCopy()`](https://lsr.djnavarro.net/reference/copy.md)
  [`rowCopy()`](https://lsr.djnavarro.net/reference/copy.md) : Copy a
  vector into a matrix

## Visualisation

A simple plotting function for displaying frequency and proportion data
as bar charts.

- [`bars()`](https://lsr.djnavarro.net/reference/bars.md) : Grouped bar
  plots with error bars

## Workspace utilities

Helper functions for inspecting and managing the R workspace, and for
miscellaneous statistical tasks not covered elsewhere.

- [`who()`](https://lsr.djnavarro.net/reference/who.md) : Contents of
  workspace
- [`modeOf()`](https://lsr.djnavarro.net/reference/mode.md)
  [`maxFreq()`](https://lsr.djnavarro.net/reference/mode.md) : Sample
  mode
- [`aad()`](https://lsr.djnavarro.net/reference/aad.md) : Mean absolute
  deviation
- [`rmAll()`](https://lsr.djnavarro.net/reference/rmAll.md) : Remove all
  objects from the workspace
- [`unlibrary()`](https://lsr.djnavarro.net/reference/unlibrary.md) :
  Unload a package
- [`importList()`](https://lsr.djnavarro.net/reference/importList.md) :
  Import a list into the workspace
- [`standardCoefs()`](https://lsr.djnavarro.net/reference/standardCoefs.md)
  : Standardised regression coefficients
- [`print(`*`<whoList>`*`)`](https://lsr.djnavarro.net/reference/print.whoList.md)
  : Print workspace summary

# Articles

### Learning lsr

- [A guided overview of
  lsr](https://lsr.djnavarro.net/articles/overview.md):

  A hands-on introduction to the lsr package for students and readers of
  Learning Statistics with R.

- [A critical commentary on
  lsr](https://lsr.djnavarro.net/articles/commentary.md):

  An honest assessment of the lsr package: what it was designed to do,
  where it falls short, and what to use instead.