Shiny Apps

January 11, 2013
By

(This article was first published on Data, Evidence, and Policy - Jared Knowles, and kindly contributed to R-bloggers)

I have been working on developing some interactive tools for demonstrating statistical principles. The advent of the shiny framework for R from the RStudio team has made this very easy to do. These demos are still in the development stage, but they are designed to help refresh statistical knowledge for applied folks now working more and more with data in their jobs.

A link to each demo online, where you can use it, and a link to the code so you can run it on your local machine or clone it and modify it on your own is below. There is also the R code to run the demo locally on your machine.

Demos:


Shiny is great!

Coin Flipping

http://glimmer.rstudio.com/wisconsindpi/coin/

https://gist.github.com/4484930

To run this Gist locally, if you have R, just run:

library(shiny)
runGist('4484930')

Election Polls

http://glimmer.rstudio.com/wisconsindpi/538

https://gist.github.com/4484951

library(shiny)
runGist('4484951')

Correlations

http://glimmer.rstudio.com/wisconsindpi/correlation

https://gist.github.com/4484910

library(shiny)
runGist('4484910')

Moments of Distributions

http://glimmer.rstudio.com/wisconsindpi/distribution

https://gist.github.com/4484886

library(shiny)
runGist('4484886')

Draws from a Normal

http://glimmer.rstudio.com/wisconsindpi/normality

https://gist.github.com/4484868

library(shiny)
runGist('4484868')

Sampling Methods

http://glimmer.rstudio.com/wisconsindpi/sampling

https://gist.github.com/4484845

library(shiny)
runGist('4484845')

NFL Kicking and Probability

http://glimmer.rstudio.com/wisconsindpi/sports

https://gist.github.com/4484754

library(shiny)
runGist('4484754')

To leave a comment for the author, please follow the link and comment on his blog: Data, Evidence, and Policy - Jared Knowles.

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