MAT-24306 Advanced Statistics for Nutritionists

Course

Credits 6.00

Teaching methodContact hours
Lecture30
Tutorial14
Practical24
Course coordinator(s)dr. B Engel
Lecturer(s)dr. EJH Korendijk
ir. SLGE Burgers
dr. B Engel
dr. SK Schnabel
dr. ir. EPJ Boer
dr. LMW Akkermans
Examiner(s)dr. B Engel

Language of instruction:

English

Assumed knowledge on:

MAT-14303 Basic Statistics or MAT-15403 Statistics 2.

Continuation courses:

Contents:

Note: This course can not be combined in an individual programme with MAT-20306 Advanced Statistics and/or MAT-25303 Advanced Statistics for Distance Learning.

This course covers several more advanced statistical models and associated designs, and techniques for statistical inference, as relevant to nutritional studies. The main topics are categorical data, (multiple) regression, analysis of variance (including multiple comparisons), analysis of covariance, and (some) variance components models. The aims of an analysis, the model assumptions, the properties (and limitations) of the models and associated inferential techniques and the interpretation of results in terms of the practical problem will be discussed. Focus will be upon students gaining an understanding of the model ingredients, an (intuitive) understanding of inferential techniques, insight into data structures and implications for choice of model and analysis. Students will be able to perform analysis of data with statistical software, i.e. with R and SPSS.

Learning outcomes:

After successful completion of this course students are expected to be able to:
- comprehend basic ideas of statistical inference, experimental design and data collection for experimental and observational studies as relevant to nutritional studies;
- determine an appropriate statistical model and associated inference procedure, given the description of the experiment, the research question and the type of data;
- carry out the analyses, with the help of SPSS or R, interpret the results, and formulate conclusions in terms of the actual problem.

Activities:

The course consists of:
- class-work;
- studying a handbook;
- practical work using SPSS and R (computer practicals are mandatory).

Examination:

- written open book test with open questions, which needs to be passed (contribution to final mark 100%).
The computer practical is compulsory and has to result in a pass, otherwise the test result is withheld.

Literature:

R. Lyman Ott; Michael T. Longnecker. (2010). An Introduction to Statistical Methods and Data Analysis. 6th ed. or 7th ed.
Lecture notes are available in English (available at the WUR-shop).

ProgrammePhaseSpecializationPeriod
Compulsory for: BVGNutrition and HealthBSc3MO+4MO