Module 4: Applied Linear Regression

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

Dates

Tuesday evenings in February and March 2018: February 27, March 6, 13, 20 and 27, 2018 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 January 26, 2018.

Venue

Faculty of Science, Site Sterre, Krijgslaan 281, Building S9, Ghent.

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 SPSS software. If preferred, participants can use SAS or R.

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 to participants with a university degree at the bachelor level or an equivalent degree.
Please note: For UGent PhD students it is no longer necessary to succeed in this exam to be able to incorporate the course in the DTP.

Incorporation in DTP and reimbursement from DS for UGent PhD students

As a UGent PhD student, to be able to incorporate this 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 January 26, 2018.

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.

Recommended handbook (optional):
"Applied Linear Statistical Models", M.H. Kutner, C.J. Nachtsheim, J. Neter and W. Li, 5th ed. (2004), McGraw-Hill, ISBN 978-0071122214.

Please note that this is the same book as recommended for Module 3 "Analysis of Variance".

Fees

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

EmploymentModule 4BookExam
Industry/Private sector1 800 70 30
Non-profit, government outside AUGent2 360 70 30
(Doctoral)student outside AUGent2 280 70 30

1 If three or more employees from the same company enrol simultaneously for this course a reduction of 10% on the module price is taken into account.

2 AUGent staff and AUGent doctoral students who pay through use of an SAP internal order/invoice can participate at these special rates.

Enrol for this course