Overview

This practical workshop will introduce you to the MATLAB programming language and how to use it to carry out data analysis.

You'll learn about importing data, statistical analysis, graphical representation, and inbuilt MATLAB applications.

It's suitable for those with little or no experience of MATLAB, or those who want a refresher. You must have a basic knowledge of statistics.

You can take this course either online, or face to face.  

Course content

This course covers the following topics:

• Getting started with the MATLAB interface
• Basic MATLAB commands: objects, functions, help and operations
• Creating and importing data in MATLAB
• Basic data manipulation in MATLAB
• Descriptive statistics
• Graphs
• Significance tests
• Overview of MATLAB applications
• Bootstrapping (time permitting)
• Regression Analysis (time permitting)

You'll be expected to have a basic understanding of statistical concepts (such as summary statistics, p-values, confidence intervals and simple regression) as these won't be taught during this workshop.

Computers and software

You'll need to have a recent version of MATLAB installed on your computer (ideally MATLAB 2017a or higher).

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)

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

Cancellations

Read the cancellation policy for this course on the ICH website. Please send all cancellation requests to the course administrator.

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 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 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 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.  

Course information last modified: 27 Mar 2024, 13:46