# MAT-24306 Advanced Statistics for Nutritionists

## Course

Credits 6.00

 Teaching method Contact hours Lecture 30 Tutorial 14 Practical 24
 Course coordinator(s) dr. B Engel Lecturer(s) dr. LMW Akkermans dr. ir. EPJ Boer dr. SK Schnabel dr. EJH Korendijk ir. SLGE Burgers dr. B Engel dr. J Engel dr. MJ Paulo dr. ir. J van Heerwaarden Examiner(s) dr. B Engel

English

### Assumed knowledge on:

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

### 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).

Programme Phase Specialization Period BVG Nutrition and Health BSc 3MO+4MO