Overview

This course aims to familiarise participants with the R interface and the R language in order to enable them to conduct statistical analysis.

Content

This self-paced course is aimed at researchers who want to learn how to use the statistical software R to conduct statistical analysis.

You'll 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

Learning outcomes

At the end of the course, you'll be able to conduct a basic statistical analysis in R using your own data or data supplied in the course materials.

You should have reasonable confidence in further independent progress through access to help files.

By the end of the course you 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.

Course structure and teaching

This is a 6 hour online, self-paced course that includes:

• Full electronic notes
• Short lecture videos (recorded outside of the classroom with screen recordings and annotation) that follow closely with the notes
• Interactive quizzes for each chapter
• Revision summaries
• Support will also be available through a forum, where you can ask questions related to the course materials.

Entry requirements

A basic level of statistical literacy is required as a prerequisite. You should have a basic understanding of standard errors, p-values and confidence intervals.

If you've completed the five-day Introduction to Statistics and Research Methods course then you'll have the necessary skills.

Cost and concessions

The standard price is £100.

A 50% discount is available for UCL staff, students, alumni. If you're eligible for a discount, email ich.statscou@ucl.ac.uk before booking to be sent the discount code.

The course is available for free to those associated with the Institute of Child Health or Great Ormond Street Hospital, and SLMS doctoral students. Please also email ich.statscou@ucl.ac.uk to gain a booking code.

Certificates

You can download a certificate of participation once you have completed all the session quizzes.

Find out about other statistics courses

CASC's stats courses are suitable for anyone requiring an understanding of research methodology and statistical analyses. The courses allow non-statisticians to interpret published research and/or undertake their own research studies. Find out more about CASC's full range of statistics courses.

Course team

Dr Dean Langan

Dean works as a lecturer, jointly based within the School of Life and Medical Sciences (SLMS) and the Centre for Applied Statistics Courses (CASC) at UCL. He has a Bachelor’s degree in Mathematics from University of Liverpool, a Master's degree in Medical Statistics from University of Leicester, and a PhD from University of York for his research in statistical methods for random-effects meta-analysis. He's worked as a statistician on a number of clinical trials related to stroke and myeloma at the Clinical Trials Research Unit in Leeds. His specialist areas include statistical methods for meta-analysis, R programming, clinical trial methodology and research design.

Course information last modified: 23 Oct 2023, 16:00