Short courses


Statistics and Research Methods: an Introduction

  • 9:30am to 5pm
  • 5 days


This five-day short course will give you a comprehensive introduction to the fundamental aspects of research methods and statistics. It's suitable for those new to quantitative research.

You'll look at topics ranging from study design, data type and graphs through to choice and interpretation of statistical tests - with a particular focus on standard errors, confidence intervals and p-values.

This course takes place online, over five days (9:30am to 5pm). You can also take this course over 10 evenings. There is also a self-paced, online version of this course that you can register for and start at any time. 

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).

Course content

During this basic introductory course in research methodology and statistical analyses you'll cover a variety of topics.

This is a theory-led course, but you'll be given plenty of opportunities to apply the concepts via practical and interactive activities integrated throughout.

The topics covered include:

  • Introduction to quantitative research
  • Research question development
  • Study design, sampling and confounding
  • Types of data
  • Graphical displays of data and results
  • Summarising numeric and categorical data
  • Numeric and categorical differences between groups
  • Hypothesis testing
  • Confidence intervals and p-values
  • Parametric statistical tests
  • Non-parametric tests
  • Bootstrapping
  • Regression analysis

Many examples used in the course are related to health research, but the concepts you'll learn about can be applied to most other fields.


The course is suitable for those new to quantitative research.

Learning outcomes

By the end of this course you should have a good, practical understanding of:

  • research design considerations (question formulation, sample selection and randomisation, study design, and research protocols)
  • data types, and appropriate summaries and graphs of samples and differences
  • standard errors, confidence intervals and p-values
  • parametric and nonparametric assumptions and tests
  • how to select an appropriate statistical test

Cost and concessions

The fees are:

  • External delegates (non UCL) - £750
  • UCL staff, students, alumni - £375*
  • ICH/GOSH staff and doctoral students - free

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


You can request a certificate of attendance for all of our courses 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)


Read the cancellation policy for this course on the ICH website. Please send all cancellation requests to ich.statscou@ucl.ac.uk

Find out about CASC's 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 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.

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.

Professor Angie Wade - Course Lead

Professor Angie Wade - Course Lead

Angie, Director of the Centre for Applied Statistics Courses (CASC), has been involved in the provision of statistical training to medically based non-statisticians for 25 years. She has a first class Bachelor’s degree in Mathematics and a Master's degree in Applied Statistics from UCL, and a PhD Statistics in the development of likelihood based models for the construction of covariate-related centiles. She joined GOS ICH in 1990, began the development of CASC in 2008 and was ICH’s first teaching professor. She's an active member of local teaching committees, previously chaired an MSc examination board and is currently a member of the UCL Academic Board Education Committee.

Learner reviews

"All sessions were exceptionally organised and presented in a clear and engaging style. The lecturers were incredibly knowledgeable and flexible and patient to the different levels of understanding in the room. The key concepts of making inferences set out at the beginning and carried throughout were especially helpful."

"Explaining the visual representation of data was very useful, as was having examples in the workbooks to learn from and 'correct'."

"The most memorable session for me was the one about significance testing. I am sure it will be very useful in my practice."

Course information last modified: 25 Jan 2022, 17:24