Overview
A package that includes functions that I find useful for teaching statistics as well as actually practicing the art. They typically are not “new” methods but rather wrappers around either base R or other packages and concepts I’m trying to master. Currently contains:
Plot2WayANOVA
which as the name implies conducts a 2 way ANOVA and plots the results usingggplot2
PlotXTabs
which as the name implies plots cross tabulated variables usingggplot2
neweta
which is a helper function that appends the results of a Type II eta squared calculation onto a classic ANOVA tableMode
which finds the modal value in a vector of dataSeeDist
which wraps around ggplot2 to provide visualizations of univariate data.OurConf
is a simulation function that helps you learn about confidence intervals
Installation
# Install from CRAN
install.packages("CGPfunctions")
# Or the development version from GitHub
# install.packages("devtools")
devtools::install_github("ibecav/CGPfunctions")
Usage
library(CGPfunctions)
will load the package which contains 4
functions:
SeeDist
will give you some plots of the distribution of a variable
using ggplot2
Mode
is a helper function that simply returns one or more modal values
neweta
is a helper function which returns a tibble containing AOV
output similar to summary(aov(MyAOV)) but with eta squared computed and
appended as an additional column
The Plot2WayANOVA
function conducts a classic analysis using existing
R functions and packages in a sane and defensible manner not necessarily
in the one and only manner.
OurConf
is a simulation function that helps you learn about confidence
intervals
Credits
Many thanks to Dani Navarro and the book > (Learning Statistics with
R)
whose etaSquared function was the genesis of neweta
.
“He who gives up safety for speed deserves neither.” (via)
A shoutout to some other packages I find essential.
- stringr, for strings.
- lubridate, for date/times.
- forcats, for factors.
- haven, for SPSS, SAS and Stata files.
- readxl, for
.xls
and.xlsx
files. - modelr, for modelling within a pipeline
- broom, for turning models into tidy data
- ggplot2, for data visualisation.
- dplyr, for data manipulation.
- tidyr, for data tidying.
- readr, for data import.
- purrr, for functional programming.
- tibble, for tibbles, a modern re-imagining of data frames.
Leaving Feedback
If you like CGPfunctions, please consider leaving feedback here.
Contributing
Contributions in the form of feedback, comments, code, and bug reports are most welcome. How to contribute:
- Issues, bug reports, and wish lists: File a GitHub issue.
- Contact the maintainer ibecav at gmail.com by email.