M5-Exploiting Sources of Variation in your Data: the ANOVA Approach
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.
Fees and registration
Fees and registration form are available on the website of the Academy for Lifelong Learning of the Faculty of Sciences (ICES, UGent).
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 3 of this year's program. Some R skills are advised consistent with the course content of Module 1 of this year's program.
Exam / Certificate
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 is an on campus course. We offer blended learning options if, exceptionally, you can't attend a session on campus.
5 Tuesday evenings in January and February 2023: January 10, 17, 24 and 31, February 7, 2023, from 5.30 pm to 9.30 pm
Faculty of Science, Campus Sterre, Krijgslaan 281, 9000 Gent
Access to handouts and data files
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...