Foundations of Data Analysis with R

Overview

This self-paced course is aimed at researchers who want to learn how to use the statistical software R to conduct statistical analysis. Delegates will be expected to have a basic understanding of common statistical tests and concepts as these will not be taught during this course. The topics covered using R will include:

• Introduction to the R platform and interface
• Introduction to basic scripting commands
• Input of data sets
• Summary measures
• Graphical displays
• Statistical tests (e.g. t-test)
• Add-ons and packages in R
• Help in R

A basic level of statistical literacy is required as a prerequisite. In particular, delegates should have a basic understanding of standard errors, p-values and confidence intervals. Those who have completed the five-day 'Introduction to Statistics and Research Methods' course run frequently by the Centre for Applied Statistics Courses (CASC) team will be equipped.

Learning Outcomes

At the end of the course, delegates should be able to conduct a basic statistical analysis in R using their own data or data supplied in the course materials. Delegates should have reasonable confidence in further independent progress through access to help files. More specifically, delegates should:

• Be familiar with the Rstudio interface and menu options.
• Have the ability to use R as a basic calculator
• Understand the general structure of the language including objects, the use of brackets and functions.
• Be able to subset and manipulate the data into a format ready for statistical analysis
• Run functions to create basic summary statistics of the data, produce graphs of a publishable standard and perform statistical significance tests.
• Have confidence in learning and installing additional packages.