Module 8 - Exploiting Sources of Variation in your Data: the ANOVA Approach
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To emphasize the practical approach in this course all classes will take place in a pc room.
Analysis of variance (ANOVA) is a statistical tool used in the comparison of means of a random variable over populations that differ in one or more characteristics (factors), e.g. treatment, age, sex, subject, etc.
First, we cover one-way ANOVA, where only one factor is of concern. Depending on the type of the factor, the conclusions pertain to just those factor levels included in the study (fixed factor model), or to a population of factor levels of which we observed a sample (random effects model).
In two-way and multi-way ANOVA where populations differ in more than one characteristic, the effects of factors are studied simultaneously. This yields information about the main effects of each of the factors as well as about any special joint effects (factorial design).
We also consider nested designs, where each level of a second (mostly random) factor occurs in conjunction with only one level of the first factor. One special challenge in multi-way ANOVA lies in verifying the assumptions that must be satisfied.
In this course we will focus on correct execution of data analysis and understanding its results. We pay attention to expressing these conclusions in a correct and understandable way.
The different methods will be extensively illustrated with examples from scientific studies in a variety of fields.
Exercises are worked out behind PC using the R software.
This course targets professionals and investigators from diverse areas, who need to use statistical methods in the collection and handling of data in their research, in particular for assessing the effect of e.g. different treatments.
Participants are expected to have an active knowledge of the basic principles underlying statistical strategies, at a level equivalent to Module 4 of this year's program. Some R skills are advised consistent with the course content of Module 2 of this year's program.
If you take part in 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.
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...
This is an on campus course. We offer blended learning options if, exceptionally, you can't attend a session on campus.
Faculty of Science, Campus Sterre, Krijgslaan 281, 9000 Ghent, Building S9, 3th floor, Room 3.4.
Access to handouts and data files
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.
*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.
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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. Open a dossier on the DS website (Application for Registration) for this course.
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.
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Please note that it is not obligatory to participate or succeed in the exam to receive a refund.
Information on "KMO-portefeuille": https://www.ugent.be/nl/opleidingen/levenslang-leren/kmo
Academy for Lifelong Learning (IPVW)
Faculty of Science
ipvw.ices@ugent.be