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 thorough 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) 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 3 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.

100% of attendees recommend this course*.
*Attendee feedback from November 2024.

Here is a sample of feedback from the course:

"Although I have previously studied statistical methods, I didn't grasp certain core concepts (such as confidence intervals). This course was very clear in explaining and exemplifying this instead of just focusing on different analysis methods. This was very useful and I will be able to use this foundation further in my own research." - course feedback, November 2024

"Clear articulation of concepts from the course providers and questions were answered in a structured and clear manner." - course feedback, November 2024

"Course tutors were very knowledgeable and approachable and were able to cover a large range of content within the available sessions." - course feedback, November 2024

"Good variation of practical and lecture sessions." - course feedback, November 2024

"I have consolidated my understanding of statistical principles. I have access to several datasets, and I am planning to relook at those with this enhanced understanding. It has also made me think about what additional questions I can answer - thank you." - course feedback, November 2024

"The content of the course was presented in a concise and clear manner, with multiple breaks at appropriate times. It was useful for one of the moderators to monitor the chat and respond to any questions during the other moderator's lecture. This ensured a good understanding of the material presented." - course feedback, November 2024

"The course was logical and each day built on the previous days learning." - course feedback, November 2024

"The explanation of key concepts and opportunity to practice learning through exercises. It was nice to do this alone / not in front of others. Working through the answers together was also helpful. Great to have regular, adequate breaks to rest and digest learning." - course feedback, November 2024

"This gave me a really good basis for understanding statistics, both how to read them when looking at research articles and what method would be best when approaching datasets." - course feedback, November 2024

"Useful basic introduction to statistics, good foundation to build on." - course feedback, November 2024

"Very well organised. The padlet worked well. Clear presentation slides. Very approachable lecturers." - course feedback, November 2024