Overview

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 over five days (9:30am to 5pm).  

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.

Eligibility

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.

Certificates

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)

Cancellations

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 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 has been co-directing CASC with its founder, Emeritus Professor Angie Wade, and has been the sole Director of CASC since January 2022. Eirini was promoted to Associate Professor (Teaching) with effect from October 2022.

Dr Chibueze Ogbonnaya

Since joining the teaching team at CASC in February 2019, Chibueze has contributed to the teaching and development of short courses. He currently leads and co-leads short courses on MATLAB, missing data, regression analysis and survival analysis. Chibueze has a BSc in Statistics from the University of Nigeria, where he briefly worked as a teaching assistant after graduation. He then moved to the University of Nottingham for his MSc and PhD in Statistics. His research interests include functional data analysis, applied machine learning and distribution theory.

Dr Catalina Rivera Suarez

Catalina has been an Associate Lecturer (Teaching) at CASC since January 2021. She has a PhD in Psychology and an MSc in Applied Statistics from Indiana University. She’s passionate about teaching courses in research methods, statistics, and statistical software. Catalina’s research focuses on studying how caregivers support the development of children's attentional control and language. She implements multilevel modeling techniques to investigate the moment-to-moment dynamics of shared joint visual engagement, as well as the quality of the language input, influencing infant learning and sustained attention at multiple timescales.  

Dr Manolis Bagkeris

Manolis has a BSc in Statistics and Actuarial-Financial Mathematics from the University of the Aegean and an MSc in Medical Statistics from the Athens University of Economics and Business (AUEB). He’s worked as a research assistant at University of Crete, UCL and Imperial College London. He’s been working at CASC since November 2021, providing short courses in research methods and statistics for people who want to develop or enhance their knowledge in interpreting and undertaking their own research. His interests include paediatric epidemiology, clinical and population health, HIV, mental health and development. He was awarded a PhD from UCL in 2021 on the topic of frailty, falls, bone mineral density and fractures among HIV-positive and HIV-negative controls in England and Ireland.

Course information last modified: 29 Aug 2024, 09:49