Exploiting Sources of Variation in your Data: the ANOVA Approach

DA2122-M5
Engels

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.

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. If preferred, participants with sufficient experience can use SPSS.

This course is part of a larger course series in Data Analysis consisting of 19 individual modules. Find more information and enroll for this module via www.ipvw-ices.ugent.be

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.

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Exploiting Sources of Variation in your Data: the ANOVA Approach

Beschrijving
  • Type of course: This is an on campus course.
  • Dates & times: November 17 and 24, December 1, 8 and 15, 2021, from 5.30 pm to 9.30 pm
  • Venue: UGent, Faculty of Sciences, Campus Sterre, Krijgslaan 281, building S9, 9000 Gent
  • Target audience: This course is aimed at biologists, bioinformaticians and statisticians interested in analysing single-cell RNA-seq datasets.
  • Exam/certificate: Participants who attend all classes receive a certificate of attendance via e-mail at the end of the course. Additionally, 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.
  • Course prerequisites: Participants are expected to have an active knowledge of the basic principles underlying statistical strategies, at a level equivalent of Module 2 'Drawing Conclusions from Data: an Introduction' of this year's program. Some R skills are advised consistent with the course content of Module1 'Getting Started with R Software for Data Analysis'.
  • Funding:
    => Our academy is recognised as a service provider for the 'KMO-portefeuille'. In this way small and middle sized businesses located in the Flanders region can save up to 30% on the registration fee for our courses. You can request this subsidy via www.kmo-portefeuille.be up until 14 calender days after the course has started.
    => UGent PhD students can apply for a full refund from their Doctoral School.
  • Reduction:
    => 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
    => Reduced prices apply to coworkers in governmental institutions, non-profit organisations and higher eduction as well as for students and the unemployed.
  • Enrolling for this course is possible via the IPVW-ICES website.