Summary (or descriptive) statistics are the first figures used to represent nearly every dataset, and are essential to the analysis process. This tutorial will explore the ways in which R can be used to calculate summary statistics, including the mean, standard deviation, range, frequencies and proportions. We will also explore some of R’s graphic capabilities and create summary plots such as scatterplots, histograms, bar charts and box and whisker plots.

This tutorial assumes no knowledge of R programming, although attendees will be expected to be familiar with using spreadsheets for data entry and have a basic understanding of statistics.

Course description

  1. Introduction to R and its capabilities as a statistical software.
  2. Familiarisation with R Studio – Open the programme, create working directories, create and save an R script, get help for a function and interpret the help documentation.
  3. Importing different types of data into R – csv, txt, STATA, SPSS, RData formats.
  4. Exploring data – commands for descriptive statistics.
  5. Plotting data – commands for scatterplots, histograms, bar charts and box and whisker plots.
  6. Scenario 1 and 2 – using example datasets, present 2 different scenarios and ask students to summarize the data in order to answer the research question at hand.

About the trainer

Alessandra Bisquera is a member of the Unit of Medical Statistics. She works as a trial statistician on a range of clinical trials run by Kings Health Partners (i.e. Guy’s and St Thomas’, Kings’ College Hospital), as well as a statistical consultant for the School of Population Health Sciences. She has taught on both the MPH and MBBS programmes and is responsible for implementing R within the Epidemiology and Biostatistics courses.