M12 - Explaining and Predicting Outcomes with Linear Regression

Type of Course - Dates - Venue - Description - Target audience - Exam - IMPORTANT: Incorporation in DTP and reimbursement by DS
Course prerequisites - Teacher - Course material - Fees - Enrol

Type of course

 This is an on campus course, with blended learning options.

Dates

5 Thursday evenings in March 2022: March 3, 10, 17, 24 and 31, 2022 from 5.30 pm to 9.30 pm. Each lecture is followed by a hands-on practical session.
Please note: the deadline for UGent PhD students who want a refund to open a dossier on the DS website (Application for Recognition) is February 3, 2022.

Venue

 To be confirmed

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. If preferred, participants can use SPSS.

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.

Exam

Participants can, if they wish, take part in an exam. Upon succeeding in this test a certificate from Ghent University will be issued.
The exam consists of a take home project assignment. Students are required to write a report by a set deadline.

Incorporation in DTP and reimbursement from DS for UGent PhD students

As a UGent PhD student, to be able to incorporate this 'specialist course' in your Doctoral Training Program (DTP) and get a reimbursement of the registration fee from your Doctoral School (DS) you need to follow strict rules: please take the necessary action in time. The deadline to open a dossier on the DS website (Application for Recognition) for this course is February 3, 2022. Please note that opening a dossier does not mean that you are enrolled. You still need to enrol via the registration form on this site.

Please note: For UGent PhD students it is no longer necessary to participate/succeed in this exam to be able to incorporate the course in the DTP.

Course prerequisites

Participants are expected to have an active knowledge of the basic principles underlying statistical strategies, at a level equivalent to the "Introductory Statistics" course of this program.

Teacher

Foto Dries ReyndersDries 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

Copies of lecture notes.

Fees

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

Employment Module 12 Exam
Industry/Private sector1 960 30
Non-profit, government, higher education staff2 720 30
(Doctoral) student, retired, unemployed2 325 30

1 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.

2 UGent staff and UGent doctoral students who pay internally via SAP or internal transfer can participate at these special rates.

Enrol for this course