Introduction to Linear and Logistic Regression Models

This 5-day course will be online and consist of a mix of live and pre-recorded sessions and practical work. Over the five days there will be approximately 14 hours of lectures and 15 hours of practicals.

By the end of the course participants should:

1. have a thorough conceptual understanding of linear and logistic regression;
2. appreciate the common threads running through these methods, including stratified analysis, different options for handling explanatory variables, and concepts such as confounding and interaction;
3. have a working knowledge of the Stata or R commands to run these models, and a thorough understanding of the output generated from such a package; and
4. know the basis on which analytical strategy and model choice is made, and how the results should be interpreted.

The course is intended for people analysing data from medical, epidemiological, and health services research, who have used simple methods such as t-tests and chi-square tests, and who now wish to use multivariable methods to control confounding, accommodate interaction, and increase statistical power.

This course will cover:

1. revision of basic methods in a statistical modelling framework;
2. terminology in regression modelling;
3. indicator variables to incorporate categorical explanatory variables;
4. univariable and multivariable regression;
5. common features of linear and logistic regression models;
6. interpretation of model coefficients as differences in means or odds ratios;
7. adjustment for confounding and exploring effect modification (interaction) in multivariable regression;
8. comparing models with Wald tests and likelihood ratio tests;
9. model assumptions; and
10. analytical strategies.

This course is taught by a team of experienced statisticians from Population Health Sciences who have taught on this and other short courses at 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.

100% of attendees recommend this course*.
*Attendee feedback from 2026.

Here is a sample of feedback from the last run of the course:

"Enthusiastic tutors who were always happy to answer questions and help. Well structured course with a mixture of lectures and practicals. Useful answer sheets so we can work back through our learning, recorded lectures so we can review them again. Quiz was great." - course feedback, February 2026

"I thought the pace of the course was about right, Stephanie and Emily were very patient and attentive and made sure to give plenty of opportunities for us to ask questions throughout the course They always strived to give clear and thorough answers to our questions and ensure no question went unanswered. I liked the mixture of learning approaches (live, pre-recorded and practical's). Overall, I thought the course provided an excellent foundation in these methods and how to apply them using standard statistical packages." - course feedback, February 2026

"Stephanie and Emily are really great teachers. Loved the quiz at the end. Lectures and practical's were all thought through very well." - course feedback, February 2026

"Teaching style was open and approachable. I felt able to ask questions and we acknowledged what was difficult about the content." - course feedback, February 2026

"The tutors were knowledgeable and experienced. I appreciated her pace; although some of the content was challenging to absorb, it was delivered effectively. We also had many practice sessions. I now feel much more confident working with my dataset." - course feedback, February 2026

"This course has given such a good overview and detail into the principles I feel a lot more confident doing the analysis. The practical sessions in particular were very useful and the structure of having the lecture then practical worked really well to put the learning into practice." - course feedback, February 2026

"This was an excellently organised course - I particularly liked the blackboard set up that we had with all resources easy to find and access, and the ability to ask questions throughout talks, on the online panel and at the daily Q&A. It was nice to have dedicated support for both STATA and R users." - course feedback, February 2026