Learn R Programming


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teachingApps is a software package for crowd-sourcing the creation of math & stats-based web apps. The goal of the package is to make teaching and learning complex math/stats concepts really fast and really easy.

In this talk Maj Jason Freels (ENV) presents some of the 135 apps that have already been built into the package and outlines how these apps can be used to:

A) Present four layers of information simultaneously:

1) Math/Stats concepts through interactive visualizations

2) Computer programming skills - with R (Python coming soon)

3) LaTeX equation typesetting with <a target=' ' href='https://www.mathjax.org/'><b>MathJax</b></a>

4) App development using HTML5, CSS3, and <a target=' ' href='http://shiny.rstudio.com/'><b>Shiny</b></a><br/>

B) Integrate into existing lecture materials (in-res & distance learning)

+ PowerPoint/Prezi/Keynote presentations

+ PDF/Beamer presentations

+ HTML presentations

+ Video Presentations

C) Combine teaching materials from SME's

+ Text

+ Equations

+ Images/Videos

+ Code

+ Shiny Apps

D) Ensure math/stat content is presented consistently across courses

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Version

Install

install.packages('teachingApps')

Monthly Downloads

40

Version

1.0.8

License

GPL (>= 2)

Issues

Pull Requests

Stars

Forks

Maintainer

Jason Freels

Last Published

May 13th, 2020

Functions in teachingApps (1.0.8)

add_options

Pass objects and customization options to a shiny app
digau

The Inverse Gaussian Distribution
Birmbaum-Saunders

The Birmbaum-Saunders Distribution
create_logo

Create a branding logo for a teachingApp
spgeng

R interface for GENG cdf;
sgquan

R interface for GENG cdf
dgets

The Generalized Threshold Distribution
inst

Get the installation path of a package
teachingApps-package

teachingApps: Apps for Teaching Statistics, R Programming, and Shiny App Development
jkf.par

Custom par function
add_logo

Adds a branding logo to the footer of a navbarPage app
gadget_clean_columns

Visually remove columns from data set
gadget_lm

Function Title
spmlgeng

R interface for gng log(1-cdf)
teachingApp

Render a teachingApp With Options
Largest Extreme Value

The Largest Extreme Value Distribution
Four Parameter Beta

The Four Parameter Beta Distribution
add_update

Add an update to a shiny app
add_ui

Add the UI of one app within the UI of another app
add_theme

Add a bootswatch color theme to an app
Smallest Extreme Value

The Smallest Extreme Value Distribution
sgpdfl

R interface for GENG cdf;
dgeng

The Generalized Gamma Distribution
degengl

The Extended Generalized Gamma Distribution
add_rmd

Add an rmarkdown file to an app
add_server

Add the server of one app to the server of another app
add_css

Add teachingApps CSS style rules to an app
add_packages

Install and load an R package
dgoma

The Gompertz Makeham Distribution