Statistics for Healthcare Professionals – The Seven Deadly Statistical Sins

**Discounts are available for this course, including fully funded places for staff and students of University of Edinburgh or NHS Lothian**

Delivered over two sessions via MS Teams.

Session 1: Foundational Statistics for Healthcare ProfessionalsThis first session is a practical introduction to medical statistics for healthcare professionals who routinely need to understand, interpret, and critically appraise statistical data, but do not necessarily need to perform statistical analysis beyond very basic examples.The emphasis throughout is on thinking statistically, not on performing complex calculations. Participants will learn how to ask the right questions of data, recognise misleading analyses or presentations, and interpret statistical results with appropriate caution and clinical judgement.

This session focuses on understanding data, choosing appropriate summaries and visualisations, and interpreting uncertainty. It is aimed at building confidence with the basic language and logic of statistics used in medical research.

Session 2: Applied Statistics for Healthcare ProfessionalsThis second session focuses on interpreting statistical analyses and conclusions as they commonly appear in medical publications, reports, and audits.

As with the foundational session, the emphasis is on interpretation and judgement rather than calculation. Participants will learn how to assess statistical claims critically, recognise over-confidence or misuse of methods, and understand what statistical results do and do not justify.

This session focuses particularly on statistical inference, common hypothesis tests, and how advanced-looking methods should be interpreted rather than feared or blindly trusted.

If you want to place an order on behalf of someone else, please email education@edinburghCRF.ed.ac.uk.

If this course is fully booked, please email education@edinburghCRF.ed.ac.uk to be added to the waiting list (please include your name, course name and course date).  

By the end of session one, participants should be able to:

• Describe different data types commonly encountered in medical research;
• Choose appropriate graphical displays to explore and understand data;
• Describe different measures of average, and explain when and why each is appropriate;
• Distinguish between absolute and relative measures of effect;
• Critically assess whether a precise and apparently strong statistical result is likely to matter in terms of clinical practice, service design, or research conclusions.

By the end of session 2, participants should be able to:

• Explain why the distribution of data matters, and recognise the practical importance of the Normal distribution;
• Explain what a p-value represents, when it may be useful, and when it is likely to be misleading or irrelevant;
• Confidently assess comparative effectiveness (e.g. whether Drug X or Drug Y works better) using a realistic simulated example;
• Deconstruct and critically appraise the statistical conclusions of a typical medical publication;
• Understand, at a conceptual level, the purpose and limitations of some advanced statistical techniques increasingly seen in modern medical research. 

Please note: the course content and examples relate mainly to medical data, but cover statistical concepts which will be broadly applicable to anyone.

This course is designed for academic, public sector and charity workers and we are offering it at a discounted price for people working in those sectors. It may also be possible to offer places to commercial organisations – please email education@edinburghCRF.ed.ac.uk for further information about availability, applicable booking fees and how to book. 

There are no specific entry requirements for this course.