Introduction to R
A course in statistical methods using R, with alternating lecture and lab sessions so that skills are applied right after being learnt.
Thursday 28 – Friday 29 November 2019
Thursday 27 – Friday 28 February 2020
With the exception of the final section on regression, the only prerequisite for this course is numerical common sense! Having completed a first-year university-level in statistics would be helpful for this last session at least, but is not a prerequisite.
This course assumes that participants will have no prior experience with R. On the first day we will begin with the basics: using R as a calculator; reading in data from a file; and generating summary statistics and contingency tables. With the basics under our belts, we will begin unveiling some of the power of R in manipulating those very large data sets too unwieldy to deal with, in the introduction of in-built R functions that provide shortcuts for performing the same operation across many columns, or rows, of a data set simultaneously.
On the second day we will discuss optimal visual displays for presenting information from different variable types (e.g. continuous, count, categorical, etc.) as we take an in-depth tour of generating publication-quality graphics in R. This will include:
- Boxplots, scatterplots, and bar charts, including legends
- Plots presenting information from multiple variables simultaneously
- The ggplot2 package for R, for even more sophisticated graphical displays
Finally, we will demonstrate how to use R to fit regression-type models to data.
We have simplified our fee structure to make it easier to show up front. We no longer have an earlybird period, and the fees for this course are simply: