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R: an Introduction

  • 5 hours
  • 1 day
  • 4 May 2020

Overview

This one-day course is aimed at researchers who want to learn how to use the statistical software R.

You'll be introduced to the R interface and the R language in order to conduct statistical analysis - from reading-in your datasets to performing all mainstream statistical tests.

You can also take this course over two evenings.

This course is run by UCL's Centre for Applied Statistics Courses (CASC), part of the UCL Great Ormond Street Institute of Child Health (ICH).

Course content

 The topics covered using R will include the following:

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

Eligibility and pre-course preparation

You'll be expected to have a basic understanding of common statistical tests and concepts as these won't be taught during this workshop.

You can use the centre's computers, or bring your own laptop with R installed (you'll be sent step-by-step installation guidelines two weeks before the course).

Learning outcomes

By the end of this course you should be able to:

  • feel more familiar with the R interface and language
  • read existing datasets into R or create new ones
  • edit and save changes in existing data
  • summarise and graphically display data
  • perform all conventional statistical analysis tests

Cost and concessions

The fees are as follows:

  • External delegates (non UCL) - £200
  • UCL staff, students, alumni (including ICH/GOSH) - £100*

* valid UCL email address and/or UCL alumni number required upon registration

Prices include printed course materials, refreshments and lunch.

Certificates

You can request a certificate of attendance for this course once you've completed it. Please send your request to ich.statscou@ucl.ac.uk

Include the following in your email:

  • the name of the completed course for which you'd like a certificate
  • how you'd like your name presented on the certificate (if the name/format differs from the details you gave during registration)

Cancellations

You can cancel your booking up to five working days before the start of the course for a full refund, but please give as much notice as possible. Places cancelled or changed after this point won't be eligible for a refund. Please send all cancellation requests to ich.statscou@ucl.ac.uk

Find out about other statistics courses

CASC's stats courses are for anyone requiring an understanding of research methodology and statistical analyses. The courses will 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, and the continuing statistics training scheme (book six one-day courses and get a seventh free.)

Course team

Dr Eirini Koutoumanou - Course Lead

Dr Eirini Koutoumanou - Course Lead

Eirini has a BSc in Statistics from Athens University of Economics and Business and an MSc in Statistics from Lancaster University (funded by the Engineering and Physical Sciences Research Council). She joined UCL GOS Institute of Child Health in 2008 to develop a range of short courses for anyone interested in learning new statistical skills. Soon after, CASC was born. In 2014, she was promoted to Senior Teaching Fellow. In 2019, she successfully passed her PhD viva on the topic of Copula models and their application within paediatric data. Since early 2020 she’s been co-directing CASC with its founder, Professor Angie Wade.

Dr Dean Langan - Course Lead

Dr Dean Langan - Course Lead

Dean is a Senior Teaching Fellow in CASC. 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.

Learner reviews

"Superb teaching - thank you! Progressed at the right pace."

"Great trainer who didn't assume anything about peoples' pre-knowledge"

"Really useful introduction - much better than trying to read about it yourself. Will try to follow on with regression in R to get more teaching on the package."

"Very enjoyable! Good examples."

"Excellent style of teaching: covered basics but at very good pace and without being patronising. Thank you"

"Great delivery by the presenter. Very clear and examples were very understandable across disciplines. The content was very clear. Help and explanations were also very clear."

"Very practical tips for using R were enormously helpful, and not the kind of thing that the textbooks seem to cover at all well."

"A very, very good course, led by 2 very good facilitators/teachers. Everything was clear and delivered efficiently and on time. Really great course and I would highly recommend."

Course information last modified: 21 Feb 2020, 09:26