Applied Data Analysis and Programming Using MATLAB

Note:This course will be delivered in hybrid mode, i.e. the in-person lecture will be transmitted live on zoom. The face-to-face part of the hybrid courses will go ahead conditional on at least 5 participants registering for this mode of delivery. Few classes may be delivered exclusively online, so please check under the Future dates tab for clarification. The online part of the class will be supported by its own dedicated teaching staff (along with the lead lecturer), therefore participants can expect the same level of group and individual support as the face-to-face class. You will be able to choose your preferred mode of attendance (face-to-face or online) during registration.

Details

This course aims to introduce delegates to the MATLAB programming language for data analysis; begins with a brief overview of the MATLAB interface, then moves on to importing data, statistical analysis, graphical representation, and inbuilt MATLAB applications. While no prior knowledge of MATLAB programming is required, it is essential that delegates have a basic understanding of statistical concepts such as summary statistics, p-values, confidence intervals and simple regression. 

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)

Please note: this is not a statistical theory course, it is intended to teach delegates about the MATLAB software. As such, dedicated time cannot be given to describing and explaining theory and statistical tests (these are taught on our course - ‘Introduction to research methods and statistics’).

Prior to attending please ensure you have a recent version of MATLAB installed (ideally MATLAB 2017a or higher) on your computer.

Fees

Course fees

* Valid UCL email address and/or UCL alumni number required upon registration. Please note, this category does not include hospital staff unless you hold an official contract with the university.

Cancellations: Cancellation Policy 

Future Dates (day)

^We recommend logging in 10 minutes prior to the scheduled start time to access materials and ensure the course can start promptly.

Future Dates (evening)

^We recommend logging in 10 minutes prior to the scheduled start time to access materials and ensure the course can start promptly at 5.00pm.

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Bespoke courses

If you are part of a team/organisation that would like statistics training, we can arrange extra dates for our existing courses or prepare something more bespoke.

Enquire about Bespoke Courses

Come to 6 day-courses, get a 7th free! 

Once you have attended 6 short-courses, you’re ready to claim your 7th day-course for free (please email us to make this arrangement). Our longer introduction course counts as three towards this total.

Contact

Please see our FAQ page before making an enquiry.

Email:
Recommended for general queries/payments:
ich.statscou@ucl.ac.uk

Phone:
For general queries/payments:
+44 (0) 20 7905 2768

Address:
Centre for Applied Statistics Courses (CASC)
UCL Great Ormond Street Institute of Child Health
30 Guilford Street
London, WC1N 1EH

Other useful links 

• GOS ICH Statistical Support Service
• On-demand UCL Extend self-paced courses
• Royal Statistical Society
• Instats

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