Module 5: Analysis of Variance

Dates - Venue - Description - Target audience - Exam
Course prerequisites - Teacher - Course material - Fees - Enrol

 

Dates

Tuesday evenings: January 12, 19 and 26, February 2, 9, 16 and 23, 2016, from 5.30 pm to 9.30 pm. Each lecture, except on January 12, is followed by a hands-on practical session in SPSS.

Venue

Faculty of Science, Campus Sterre, Krijgslaan 281, Building S9, Ghent

Description

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 satified.

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

Target audience

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.

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.

To qualify for reimbursement from the UGent Doctoral Schools one must attend all classes and pass the exam. Additional conditions and procedure.

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.

In the first session, on January 12, 2016, these principles will be briefly reviewed. This review session is open to interested participants of subsequent modules. Participants who have recently followed the introductory course are exempt from that first session.

Teacher

Foto van lesgever Els AdriaensDr. Els Adriaens (Adriaens Consulting bvba) studied biology, obtained a PhD in pharmaceutical sciences and a master in Statistical Data Analysis at Ghent University.

She is consultant in statistical data analysis specialized in the field of the development and validation of alternatives to laboratory animals.

 

Course material

Handouts of slides.

Recommended handbook: "Applied Linear Statistical Models", Michael H. Kutner, Christopher J. Nachtsheim, John Neter and William Li, 5th ed. (2004), McGraw-Hill (ISBN 978-0071122214).

Fees

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

EmploymentModule 5BookExam
Industry/Private sector1 800 70 30
Non-profit, government, university 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