Data Science

Multivariate Analysis with R

Preliminaries Multivariate data A map Distance matrices Cluster analysis Mantel test Multidimensional scaling Principal components analysis Discriminant function analysis Epilogue Reading time: 32 minute(s) @ 200 WPM. Preliminaries At some time or another, most users of statistics find themselves sitting in front of a large pile of computer output with the realization that it tells them nothing that they really want to know.

An Introduction to R

Prologue Getting a feel for R The console Function calls and arguments HINT: Getting help Some graphics HINT: Command history and workspace Getting data into R Data frames Creating data frames HINT: Data management in R and RStudio. Exploratory data analysis Scatterplot matrix HINT: R packages Summary statistics and data screening Box plots Stem-and-leaf display Categorical variables: factors Some confirmatory analysis More graphics R scripts (command files) An R menu system: R-commander Epilogue Reading time: 22 minute(s) @ 200 WPM.

R Markdown Test

Reading time: 2 minute(s) @ 200 WPM. Yes, it doth work. The blogdown package can nicely deal with R Markdown containing embedded R code for production of statistical analyses and graphics. But. It cannot deal with R Notebooks, which contain a special flavor of R Markdown allowing for interactive display of R code alongside the results they produce. R Notebooks, when rendered into HTML, produce a special file named *.

Google Search

Reading time: 2 minute(s) @ 200 WPM. Following the directions for Google’s Custom Search Engine, with additional help from How I added search to my static blog, I have added a local search function to this website. It’s on the sidebar menu, with an adorable magnifying glass icon from Font Awesome Icons, and it basically works. This search function will, in all likelihood, probably search only the specific content of richardlent.

Video test

Reading time: 1 minute(s) @ 200 WPM. We now attempt to insert into our R Markdown file, which Hugo then renders into HTML, an mp4 video of dragonflies (insect order Odonata, in case you’re wondering) that were congregating in my front yard a few summers ago. So I’m thinking, just insert it using a regular Markdown image tag, yes? Like this: ![](/mp4/Dragonflies.mp4). And so, that worked. To center this video on the page I am using the deprecated HTML <center> tag inside of my R Markdown.

RStudio as a Research and Writing Platform

Reproducible Research Software Installation Rendering Documents in RStudio Writing and Citing in RStudio R Notebooks Reproducible Research Revisited Coda I: Python Coda II: Inspirational Quotes About Data Reading time: 22 minute(s) @ 200 WPM. R ( is a programming language and software platform for statistical computing and graphics, widely used in academia and industry (see An Introduction to R). RStudio is an integrated development environment for R.

Getting images to work

Reading time: 3 minute(s) @ 200 WPM. I was until very recently involved in an epic struggle to get the system described in Making a Website Using Blogdown, Hugo, and GitHub pages to work for me. (See also Building a Blog with Blogdown and GitHub.) I really want it to work, because it has produced the current website that you are now reading, and I’m sure you’ll agree that it is very, very beautiful, in a stark, post-apocalyptic, Mordor-esque sort of way.