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Introduction This post provides a bit of guidance for students in CSC 115 who are working on the Madhava Graph exercise in Chapter 4 of the course text. As you will recall, the statement of the problem is as follows: Recall the function madhavaPI() from Section 3.4.1. Use this function to write a function called madhavaGraph() that will do the following: given a number \(n\), the function uses ggplot2 to produce a line graph of the first \(n\) approximations to \(\pi\) using the initial terms of the Madhava series.


I tweaked a couple of simple Hugo themes for use by R-bloggers along with the blogdown package. If you prefer minimal themes you might wish to start with one of these.


My primary technical blog is hosted by Github through my User repository ( Recently I switched my generator from Jekyll to Hugo. From the User repository Github Pages requires that the site be served from the root of the repository (not from docs). Jekyll allowed us to build the site into the root, but Hugo builds into a specific directory, named public by default. Building into the root would look a bit messy, anyway.


Notes for colleagues on installation of the addinplots package.


Describes my addinplots package, a set of GUIs in the R Studio IDE for the Lattice plotting system.



Addin Plots

For use by my elementary statistics students. Provides a GUI for lattice plotting functions. Code output goes to the console or source document.

Tiger Tree

tigerTree is designed to facilitate the teaching of elementary statistics with the R programming language, especially in the RStudio integrated development environment. In particular, it provides some helper functions to permit students to build tree models using the tree package and to test these models.


A collection of data sets and functions that are useful in the teaching of statistics at an elementary level to students who may have little or no previous experience with the command line.


In Fall 2017 I am teaching the following courses:

  • CSC115: Computer Science I
  • CSC303: Fundamentals of Data Computing
  • MAT301: Discrete Mathematics
  • MAT431: Real Analysis I
  • CSC470: Topics in Computer Science: R Programming