Overview

This introductory course gives you an overview of regression types and details the application of multiple linear regression.

The main part of the course focuses on the theory behind regression analysis, in particular linear regression, and covers the formulation, interpretation and validation of linear regression models.

There are optional workshop days that allow delegates hands-on use of a statistical package (SPSS/Stata/R) to see how the theory can be applied to answer a specific research question.

This course takes place either online or in person over two or three days.  

Course content

Regression analysis is a very powerful technique that allows you to investigate the combined associations between one or more predictors and an outcome.

Some examples where this is helpful are:

• where within a trial you may wish to adjust for factors that differ between treatment groups to gauge the true effect of treatment
• in observational studies where you might want to take into account differences between the demographics or health behaviours of two or more subgroups
• when considering the combined effects of different factors, which may facilitate understanding of variation in outcome

Regression is a vital tool for any quantitative researcher.

This course takes you from the basics of types of regression to the formulation of a multiple linear regression model. Interaction terms are introduced and explained.

On the optional extra day, you'll use SPSS/Stata/R to explore how the theory taught in the first part can be applied.

Who this course is for

This course is suitable for quantitative researchers or anyone who needs an understanding of introductory-level regressions analysis.

It will also be of interest to those using alternative statistical packages as the concepts discussed throughout the course are generally applicable.

Computers and software

To take part in the optional part of the course, you'll need to have SPSS/Stata/R installed and licensed on your computer. Where possible, we recommend using a recent version of SPSS/Stata/R  for maximum compatibility with the notes provided during the course.

Learning outcomes

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

• understand the different types of regression and when these are applicable
• visualise univariable linear regression model fits
• understand the role of residuals
• understand multiple linear regression models and how these can be constructed
• decipher output from a software package

Cost and concessions

The fees are as follows:

• External delegates (non UCL) - £150 (£275 with optional SPSS/Stata/R workshop))
• UCL staff, students, alumni - £75* (£137.50 with optional SPSS/Stata/R workshop)
• ICH/GOSH staff and doctoral students - free

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

Read the cancellation policy for this course on the ICH website. 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

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.

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: 11 Apr 2024, 15:34