Short courses


Statistics and Regressions with R: an Introduction (Summer School)

  • 21 hours
  • 5 days


This five-day summer school provides an introduction to statistical analysis and the statistical programming language R.

You'll learn the fundamental principles of statistics and how to carry out your own analysis, including significance tests and regression techniques.

In practical sessions you'll learn how to use Rstudio - free software which provides a user-friendly interface for R.

This course is delivered by UCL's Centre for Applied Statistics Courses (CASC), part of the UCL Great Ormond Street Institute of Child Health (ICH). CASC run another summer school on Statistical Thinking and Data Analysis: an Introduction.

Course content

The course will cover the following topics:

  • Quantitative research study designs
  • Types of data 
  • Graphical displays 
  • Summaries of data 
  • Confidence intervals 
  • Hypothesis testing (parametric and non-parametric tests)
  • P-values
  • Regression analysis

The course will cover a number of different regression analyses, including the following:

  • Linear regression
  • Logistic regression
  • Ordinal logistic regression
  • Poisson regression
  • Negative binomial regression

Social events

As part of the summer school, you can attend a number of free social activities, including an evening reception on the first day, a dinner and a trip to see a musical.

Who this course is for

You don't need any knowledge of statistical analysis or R to attend this course.

Learning outcomes

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

  • set out a plan of analysis for a research question, accounting for all types of data involved and aspects of the question
  • choose the best way of graphically displaying data and results
  • choose the significance tests suitable to answer the research question  
  • make appropriate use of statistical inference methods
  • understand when regression methods are useful
  • choose the most suitable regression model for your analysis
  • evaluate the goodness of fit of the fitted model
  • perform appropriate model diagnostics and predictions
  • perform all the above analyses in the Rstudio software package


You'll receive a certificate of attendance when you have completed the course.

    Cost and concessions

    The standard price is £1,800.

    The fee includes:

    • a welcome pack
    • printed course materials
    • refreshments and lunches
    • social events

    The fee doesn't cover accommodation and you'll need to arrange this yourself. 


    Refunds won't be given for cancellations made within two weeks of the start date or for non-attendance.

    Cancellations made within two to four weeks of the start date will incur a fee of 25%. Please send all cancellation requests directly to the course administrator.

    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, and the continuing statistics training scheme (book six one-day courses and get a seventh free.)

    Course team

    Dr Eirini Koutoumanou

    Dr Eirini Koutoumanou

    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

    Dr Dean Langan

    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.

    Course information last modified: 1 Nov 2021, 14:39