Target audience

This course targets professionals and investigators from all areas who are involved in prediction problems or need to model the relationship between a dependent variable and one or more explanatory variables.

Description

Linear regression addresses how a continuous dependent variable is associated by one or more predictors of any type. The fact that many practical problems deal with continuous outcomes (e.g. income, blood pressure, temperature, affect) makes linear regression a popular tool, and most of us will be familiar with the concept of drawing a line through a cloud of data points.

The first two sessions of this module introduce the conceptual framework of this method using the simple case of a single predictor. Formulas and technicalities are kept to a minimum and the main focus is on interpretation of results and assessing model validity. This includes confidence statements on the predictor effect (hypothesis tests and confidence intervals), using the regression model to predict future results and verification of model assumptions.

In session 3 and 4 we allow for more than one predictor leading to the multiple linear regression model. We focus on either explanation or prediction. How to come to a parsimonious model starting from a large number of predictors will be discussed in detail. In these complex linear models special attention will be given to interpreting individual predictor effects, as they critically depend on other terms in the model and underlying relations between predictors (confounding).

In the last session a more elaborate data analysis is discussed. We touch on problems where linear regression is not appropriate and replaced by related approaches such as generalized linear models and mixed models.

Different features will be illustrated with case examples from the instructors practical experience, and participants are encouraged to bring examples from their own work.

Hands-on exercises are worked out behind the PC using the R software.

Course prerequisites

Participants are expected to have an active knowledge of the basic principles underlying statistical strategies, at a level equivalent to the Module 3 of this program.

Exam / Certificate

If you attend all 5 sessions you will receive a certificate of attendance via e-mail after the course ends.

Additionally, you can take part in an exam. If you succeed in this test a certificate from Ghent University is issued.
The exam consists of a take home project assignment. You are required to write a report by a set deadline.

Microcredential

This module is part of the microcredential 'Applied Statistics: from Basics to Regression Modelling' that consists of three modules:

• Module 3 - Drawing Conclusions from Data: an Introduction
• Module 5 - Exploiting Sources of Variation in your Data: the ANOVA Approach
• Module 9 - Explaining and Predicting Outcomes with Linear Regression

If you are planning on registering for all three modules, consider enrolling for the microcredential instead. Read more...

Type of course

This is an on campus course. We offer blended learning options if, exceptionally, you can't attend a class on campus.

Schedule

5 Thursday evenings in March 2023: March 2, 9, 16, 23 and 30, 2023 from 5.30 pm to 9.30 pm. Each lecture is followed by a hands-on practical session.

Venue

UGent, Faculty of Science, Campus Sterre, Krijgslaan 281, Ghent. Building S9, 3rd floor, pc room 3.1 (Konrad Zuse).

Teacher

Dries Reynders studied Physics and Statistical Data Analysis at Ghent University.

He is an experienced teacher and is, in that role, well trained in explaining the link between mathematics and the reality it describes. Currently, he works as statistical consultant for the Stat-Gent consortium.

Course material

Access to lecture notes and data files

Fees

A different price applies, depending on your main type of employment.

*If two or more employees from the same company enrol simultaneously for this course a reduction of 20% on the module price is taken into account starting from the second enrolment.

Register

Register for this course

UGent PhD students

As UGent PhD student you can incorporate this 'specialist course' in your Doctoral Training Program (DTP). To get a refund of the registration fee from your Doctoral School (DS) please follow these strict rules and take the necessary action in time. The deadline to open a dossier on the DS website (Application for Registration) for this course is January 10, 2023.

Opening a dossier with your DS does not mean that you are enrolled for the course with our academy. You still need to enrol via the registration form on this site.

It is you or your department that pays the fee first to our academy. The Doctoral School refunds that fee to you or your department once the course has ended.

Please note that it is not obligatory to participate or succeed in the exam.