**Jason.Bryer.org Blog - R**, and kindly contributed to R-bloggers)

Consider a pool table of length one. An 8-ball is thrown such that the likelihood of its stopping point is uniform across the entire table (i.e. the table is perfectly level). The location of the 8-ball is recorded, but not known to the observer. Subsequent balls are thrown one at a time and all that is reported is whether the ball stopped to the left or right of the 8-ball. Given only this information, what is the position of the 8-ball? How does the estimate change as more balls are thrown and recorded?

You can run the app from RStudio’s shinyapps.io service at jbryer.shinyapps.io/BayesBilliards.

The Shiny App is included in the `IS606`

package on Github and can be run, once installed, using the `IS606::shiny_demo('BayesBilliards')`

function.

Or, run the app directly from Github using the `shiny::runGitHub('IS606', 'jbryer', subdir='inst/shiny/BayesBilliards')`

function.

Source code is located here: https://github.com/jbryer/IS606/tree/master/inst/shiny/BayesBilliards

**leave a comment**for the author, please follow the link and comment on their blog:

**Jason.Bryer.org Blog - R**.

R-bloggers.com offers

**daily e-mail updates**about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...