The “learn X in 20min” series seems to be a popular amongst the viewers, so Ellis Hughes and I decided to throw together one. This week, we are walking through the basic code for a Bayesian regression model using the {rstanarm} package. Because we only keep it to 20min, we use the default priors and don’t get into any sort of complex stuff about Bayes. We do, however, discuss making predictions of point estimates and posterior distributions, and show how you can explore model uncertainty.

To watch the screen cast, CLICK HERE.

To access the code, CLICK HERE.

In our final episode of Base R plotting, Ellis Hughes and I use the {Lahman} baseball package to explore Hall of Fame Baseball players. In this episode we show how to make your Base R plots more interactive, allowing the user to click on the points within the plot and obtain information specific to the player.

To watch our screen cast, CLICK HERE.

To access our code, CLICK HERE.

Ellis Hughes and I continue our work building plots in Base R. This week, we turn our attention to various plotting approaches for visualizing the distribution of your data. We cover box plots, bar plots, histograms, and density plots.

To access our code, CLICK HERE.

To watch our screen cast, CLICK HERE.

Ellis Hughes and I continue our Base R plotting tutorial and discuss how to set up line plots, for time series and trend data. We provide a number of line plot options using the {Lahman} baseball data package.

To watch out screen cast, CLICK HERE.

To access our code, CLICK HERE.

This week, Ellis Hughes and I discuss how to get started with Base R plots. We’ve done a ton on our screen cast using {ggplot2} and {plotly}. But, there are some cool things you can do with Base R plots to make them look really nice and presentable. In this first part we discuss scatter plots and show how to go from the basic default settings into something that is more presentable.

To watch the screen cast, CLICK HERE.

To access the code, CLICK HERE.