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Funded by an FPDC (2021 - 2022) grant, this web app is built by Xuemao Zhang. The goal of the app is to promote students’ interest in R programming while learning introductory statistics. Installation and configuration are not needed as a web-based application. Students interested in coding can copy the R code in the app and paste to the R workspace installed on their PC or Mac to reproduce the data analysis results. However, the functionality is point-and-click so those uninterested in coding will not be intimidated by the features. The app was intended for students in all PASSHE (PA State System of Higher Education) schools to use. It is expected to be adopted by more undergraduate universities. Please contact me xzhang2@esu.edu if you have any suggestions or ideas to improve this web app.
DO NOT upload sensitive data to the app since security considerations have not been addressed yet.
Some R packages are used in this app for statistical data analyses. If you are interested in R programming, please install these packages by pasting install.packages(c("car","BSDA","datarium","dplyr","EnvStats","ggplot2", "rstatix"))
to the R console after R is installed on your computer.
The app has the following six menus:
The following four menus will allow users to perform basic data analyses and statistical routines after a dataset is uploaded.
The {golem}
framework is used to build the Shiny App backend.
The whole app is powered by {shiny}
.
Most data visualisations are done with {ggplot2}
.
Reproducible R code is done with the function interpolate
and package {shinymeta}
.
Ace text editor is provided by {shinyAce}
, and {rclipboard}
provides copy-to-clipboard functionality.
Excel-like data entry ability is provided by {rhandsontable}
.
Packages for data analysis include {car}
, {BSDA}
, {datarium}
, {dplyr}
, {EnvStats}
and [{rstatix}
] (https://github.com/kassambara/rstatix).
Mathematical symbols and equations are rendered using MathJax
.
The app is deployed on RStudio shinyapps.io.