rkTeaching
An R package for teaching and learning Statistics
Table of Contents
What is rkTeaching?
rkTeaching is an R package that provides a plugin for the graphical user interface RKWard adding new menus and dialog specially designed for teaching and learning Statistics.
This package has been developed and is maintained by Alfredo Sánchez Alberca asalber@ceu.es in the Department of Applied Math and Statistics of the San Pablo CEU of Madrid.
If you find out some error or have a suggestion, please, let me know it by email or opening an issue on Github.
Installation
Installation on Windows
For Windows users there is a bundle that include R, RKWard and rkTeaching.
Download last version (R versión 3.6.2, RKWard versión 0.7.1b, rkTeaching versión 1.3.0)
Once the file is downloaded, all you have to do is to execute it.
It will ask for the installation unit and directory.
It is recommended to install it on the root of unit C, that ist C:.
The installation creates a folder rkward into the installation directory. There, in the bin folder you have to execute the rkward.exe
file to start the program.
The following video tutorial shows the installation process (in Spanish).
Installation on Mac OS
To install the software on Mac OS systems, you must take the following steps:

Install R. R can be downloaded from the following links:
 R version 4.0.1 For MacOS 10.13 and higher.
 R version 3.5.3. For older MacOs versions.

Install RKWard. RKWard can be downloaded from the web http://rkward.sourceforge.net.
You have to select the MacOs distribution corresponding to your R version:

RKward version 0.7.2 (for R version 4.0.1).

RKWard version 0.7.0 (for R version 3.5.3).
After downloading it follow the installation instructions


Install the packages that rkTeaching depends on. The rkTeaching package depends on several packages that should be installed first. To install this packages you must run RKWard, open the R console and type the following commands:
install.packages(c("R2HTML","car","e1071","Hmisc","plyr","ggplot2","prob","ez","multcomp", "remotes"))

Install rkTeaching. To install the rkTeaching package you must type the following commands in the R console:
library(remotes) install_github("rkwardcommunity/rk.Teaching")
The following video tutorial shows the installation process (only for RKWard version 0.7.0).
Installation on Linux
To install the software in Mac OS systems, you must take the following steps:

Install R. R can be downloaded from the web https://cran.rproject.org/. You have to select the Linux distribution and follow the instructions there. It is required an R version 3.4 or higher.
With Debian based distributions like Ubuntu, you can install R from the command line typing the command:
sudo aptget install rbase

Install RKWard. RKWard can be downloaded from the web http://rkward.sourceforge.net. You have to select the Linux distribution and follow the instructions there.
With Debian based distributions like Ubuntu, you can install R from the command line typing the command:
sudo aptget install rkward
It is important to install versión 0.7 or higher.

Install the packages that rkTeaching depends on. The rkTeaching package depends on several packages that should be installed first. To install this packages you must run RKWard, open the R console and type the following commands:
install.packages(c("R2HTML","car","e1071","Hmisc","plyr","ggplot2","prob","ez","multcomp", "remotes"))

Install rkTeaching. To install the rkTeaching package you must type the following commands in the R console:
library(remotes) install_github("rkwardcommunity/rk.Teaching")
The following video tutorial shows the installation process (in Spanish).
Statistical procedures
Once installed a new menu Teaching
will appear in RKWard with the following statistical procedures:
 Data manipulation:
 Fiter data
 Calculate variable
 Recoding variable
 Weight data
 Frequency distributions:
 Frequency tabulation
 Bidimensional frequency tabulation
 Plots:
 Bar graph
 Histogram
 Pie graph
 Box graph
 Means graph
 Interaction graph
 Scatterplot
 Descriptive statistics
 Statistics
 Detailed calculation
 Regression:
 Linear Regression
 Non linear regression
 Regression model comparison
 Regression prediction
 Parametric tests:
 Means:
 T test for one sample
 T test for two independent samples
 T test for two paired samples
 ANOVA
 Sample size calculation for mean estimation
 Variances:
 Fisher test for two samples
 Levene test for multiple samples
 Proportions:
 Test for one proportion
 Test for two proportions
 Sample size calculation for proportion estimation
 Means:
 Non parametric tests:
 Normality tests: ShapiroWilk, Kolmogorov
 U MannWhitney test
 Wilcoxon test
 Friedman test
 KruskalWallis test
 Chisquare test
 Concordance
 Intraclass correlation coefficient
 Cohen’s kappa
 Probability:
 Random games:
 Coins
 Dice
 Cards
 Urn
 Build probability space
 Combine probability spaces
 Repeat probability space
 Calculate probability
 Random games:
 Probability distributions
 Discrete:
 Binomial
 Geometric
 Hypergeometric
 Poisson
 Continous:
 Uniform
 Normal
 Chisquare
 Student’s T
 Fisher’s F
 Discrete:
 Simulations:
 Law of rare events
Functionality

Menus and dialogs specially designed to easy the learning, ruling out noncommon options to get an simplified and intuitive interface.

All the dialogs have a wizard that guide the user step by step through the statistical procedure.

HTML output tha presents the results of the analysis in a clear and concise way.

Charts based in the modern ggplot2 package.

Computation formulas and details available for some statistical procedures.
rkTeaching is maintained by asalber.
How to cite rkTeaching?
SánchezAlberca, A. (2020). rkTeaching (version 1.3) [software]. Get from: http://aprendeconalf.es/projects/rkteaching.