Introduction to Statistics

All teaching for this 4-day course will be conducted online using Blackboard. There will be online live sessions each day including lectures and supported group work, supplemented by asynchronous materials such as recorded lectures. Participants will complete the computing practicals on their own computer, with tutor support available over Blackboard.

By the end of the course participants should be able to:

1. appreciate the role of statistical methods in clinical and public health research;
2. present quantitative data using appropriate displays, tabulations and summaries;
3. understand the key concepts of statistical inference, and appreciate the methods taught as tools within this framework;
4. select and use appropriate statistical methods with regards to the clinical question, variable types and study design;
5. understand and interpret presentations of statistical results, as produced by statistical software or presented in research journals; and
6. present the findings of a statistical analysis in a clear, concise and understandable manner.

This course is intended for those who require a grounding in the common statistical methods used in clinical and public health research, which will provide a firm foundation for further learning.

In terms of well-known statistical methods, this course covers t-tests, chi-square tests, correlation coefficients, and an introduction to linear regression. But attendees should be prepared to gain a deeper understanding of the concepts underlying these labels. If all you want to do is fire out p-values from SPSS, there are plenty of freely available YouTube videos that will tell you how to do that.

The course tutors are drawn from across the Bristol Medical School.

To make sure the course is suitable for you and you will benefit from attending, please ensure you meet the following prerequisites before booking:

Before booking this course, please make sure you read the information provided above about the target audience and prerequisites. It is important that you have access to the relevant IT resources needed for the course and meet the knowledge prerequisites to ensure you can get the most from the course.

Bookings are taken via our online booking system, for which you must register an account. To check if you are eligible for free or discounted courses please see our fees and voucher packs page. All bookings are subject to our terms & conditions, which can be read in full here.

For help and support with booking a course refer to our booking information page, FAQs or feel free to contact us directly. For available payment options please see: How to pay your short course fees.

Participants are granted access to our virtual learning platform (Blackboard Ultra) 1 to 2 weeks in advance of the course. This allows time for any pre-course work to be completed and to familiarise with the platform.

To gain the most from the course, we recommend that you attend in full and participate in all interactive components. We endeavour to record all live lecture sessions and upload these to the online learning environment within 24 hours. This allows course participants to review these sessions at leisure and revisit them multiple times. Please note that we do not record breakout sessions.

All course participants retain access to the online learning materials and recordings for 5 months after the course. 

University of Bristol staff and postgraduate students who do not wish to attend the full course may instead register for access to the 'Materials & Recordings' version of this course: Further information and bookings.

78% of attendees recommend this course*.
*Attendee feedback from December 2025.

Here is a sample of feedback from the course:

“It was a great refresher on the underlying mechanisms behind the stats reported in papers and how to calculate them." - course feedback, December 2025

“The course had a great mix of lectures and practicals. It was nice to learn about something and immediately put it into action. The two presenters Erik and Chris were also great." - course feedback, December 2025

“Quality of teaching was very good. Resources were readily accessible and it was possible to catch up using the recordings there were things I had missed or were not as clear on, in my own time." - course feedback, December 2025

“Layout of course was good especially split over a weekend. Well taught and opportunity to ask questions." - course feedback, December 2025

“I found the practical sessions the most useful and it was good to jog my memory around statistical significance, p values, standard deviations etc. I feel like these were very well explained." - course feedback, December 2025