Introduction to Statistical Programming
Academic Lead: Dr Cedric Ginestet
Instructors: Dr Ewan Carr, Mr George Vamvakas
Date: 29th October 2018 – 1st November 2018
Venue: Computer Rooms A & B, Main Building, Institute of Psychiatry, Psychology and Neurosciences (IoPPN), King's College London. View Map.
- External £600
- KCL Staff £450
- KCL Student £300
- King's Health Partners £450
- Other student £450
(That is, 50% discount to King's College London PhD students, 25% discount to other students and staff at King's College London and King's Health Partners)
Places available: 40
Last booking: 24th October 2018
BOOKING: Booking for this course has now closed.
The Statistical Programming course is focused on extending existing skills in analysing data from quantitative research in health research using R or STATA. Programming skills are particularly useful when confronted with complex and/or large datasets, when conducting regular statistical analyses, or when there is a need to adapt existing codes to your own requirements. Statistical programming expertise is increasingly needed in imaging, bioinformatics, omics, cohort and clinical trials with complex interventions.
Subject-specific: Knowledge, Understanding and Skills
At the end of the course the students should be able to demonstrate subject-specific knowledge, understanding and skills and have the ability to:
* Develop a theoretical understanding of the basics of programming;
* Understand the use and usefulness of conditionals, iterations, and functions;
* Identify appropriate methods for solving particular data manipulation problems;
* Formulate sensible programming solutions for a data set, and demonstrate an ability to check the correctness of one’s manipulations;
* Become an independent user of R and Stata, in finding help online, and demonstrate how to select appropriate packages for one’s problems.
General: Knowledge, Understanding and Skills.
On successful completion of this course the student should be able to:
* Understand and explain basic programming concepts;
* Justify and critique the use of programming solutions for real life applications;
* Show confidence in the use of R and Stata in manipulating data sets for real life application;
* Communicate ideas effectively and professionally by written, oral and visual means;
* Study autonomously and undertake activities with minimum guidance;
* Select and properly manage information drawn from books, journals, and the internet;
* Interact effectively in a group.
Please note the following:
If you would like to pay by internal transfer, please contact firstname.lastname@example.org
Your place will not be confirmed until payment has been made.
Failure cancel without sufficient notice will forfeit your course fee and access to future courses.