FTE-26306 Data Analysis Biosystems Engineering

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Studiepunten 6.00

Language of instruction:

Dutch and/or English

Assumed knowledge on:

MAT-15303 Statistics 1 and MAT-15403 Statistics 2.

Continuation courses:

FTE-25806 Research Methods Biosystems Engineering 2.

Contents:

The following topics will be addressed in the course:
- linear regression and multiple linear regression: model formulation, meaning of model parameters, checking model assumptions and prediction;
- data transformation;
- experimental design: completely randomized design, block design and factorial design. Calculating the required sample size to obtain a certain precision;
- analysis of variance and pair-wise testing;
- selection of variables (quantitative and/or qualitative) to find the optimal linear regression model (checking assumptions);
- repeated measurements;
- calibration, validation and cross-validation.
These methods are relevant for further data analysis in the biosystems engineering domain. The theory of the course will be supported by practical's in which relevant data sets from the biosystems engineering domain will be analysed.
Part of the course is the module Information literacy and is a continuation of the information literacy module in the first year of the programme. In this module the students will learn the more advanced searching techniques and strategies for relevant (scientific) papers and other information. The topic for the module will be the same as the topic for the research project in the course FTE25806 Research methods biosystems engineering.
Students will also participate in a professional assessment and, supported by staff, will translate these outcomes in the context of their current programme and future choices.

Learning outcomes:

After successful completion of this course students are expected to be able to:
- translate a research question into a statistical hypothesis;
- design the appropriate experiment given the hypothesis;
- choose an appropriate model and check the underlying assumptions;
- analyse the data with an appropriate programme;
- interpret the results of the analysis and draw conclusions with respect to the stated problem;
- perform an advanced literature and information research by using the proper search techniques and strategies and presenting the results in a correct way;
and have gained more insight into their own qualities and can relate this to choices to be made within the programme and the personal development plan (=motivation for BSc-3 programme).

Activities:

- lectures and tutorials;
- support by practical's;
- literature search and reporting;
- BSc assessment and reflection on outcome of assessment.

Examination:

- written exam;
- pass required for computer practical's;
- information literacy and BSc assessment.

Literature:

- Statistical Methods and Data Analysis by R. Lyman Ott and Michael Longnecker. 6th ed. ISBN 0495109142.
- Lecture notes (available at the WUR-shop).