(Bio)Engineering

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° 2024M11LR EN
Tags: Kort- en langlopende opleidingen

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.

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.

Course prerequisites

Participants are expected to have an active knowledge of the basic principles underlying statistical strategies, at a level equivalent to the Module 4 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:

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 February & March: February 29, March 7, 14, 21 & 28, 2024 from 5.30 pm to 9.30 pm.

Venue

Faculty of Science, Campus Sterre, Krijgslaan 281, 9000 Ghent, Building S9, 3th floor, Auditorium 3

Course material

Access to lecture notes and data files

Fees

The participation fee is 1100 EUR for participants from the private sector. Reduced prices apply to students and staff from non-profit, social profit, and government organizations. An exam fee of 35 EUR will be applied.

  • Industry, private sector, profession*: € 1100
  • Non profit, government, higher education staff: € 825
  • (Doctoral) students, unemployed: € 495

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

Registration

To register, add the course below to your shopping cart and proceed to checkout.

Is this your first registration for a Beta Academy course? In that case, you will need to create an account first. Afterward, you will receive a confirmation email to activate your account on the academy platform. You do not have to click on the activation link but can immediately return to your shopping cart to complete your course registration. If you do not receive a confirmation email for your course order, please contact our Academy for Lifelong Learning at ipvw.ices@ugent.be.

Are you currently on the Nova-academy website? To proceed with the registration, simply click on the "More information" box located on the left side.

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 9, 2024.

Opening a dossier with your DS does not mean that you are enrolled for the course with our academy. You still need to register 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 to receive a refund.

KMO-portefeuille

Information on "KMO-portefeuille": https://www.ugent.be/nl/opleidingen/levenslang-leren/kmo

Organisation

Academy for Lifelong Learning (IPVW)

Faculty of Science

ipvw.ices@ugent.be

Website

Course number:
2024M11LR
Type:
Short- en long-term programmes
Area of interest:
(Bio)Engineering, AI and Data Science, Bioengineering, Biomedical Sciences, Sciences
Language:
EN
Academic year:
2023 - 2024
Starting date:
29.02.2024
Lecturers:
Dries Reynders
Contact person:
ipvw.ices@ugent.be
More information

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