# MAT-15403 Statistics 2

## Course

Credits 3.00

 Teaching method Contact hours Tutorial 26 Practical 12 Independent study 0
 Course coordinator(s) drs. H Engel MSc RM Hu dr. ir. EPJ Boer Lecturer(s) G Mooiweer MSc RM Hu dr. ing. MPH Verouden dr. ing. M Knotters dr. LMW Akkermans drs. LCP Keizer dr. ir. EPJ Boer drs. H Engel ir. SLGE Burgers dr. CGF de Kovel dr. SK Schnabel dr. EJ Bakker H Ehlers dr ir NA Hartemink dr DJ Brus V Avagyan BJB Stout dr. J Engel S Gugushvile J van den Boom Examiner(s) drs. H Engel dr. ir. EPJ Boer

NL and/or EN

### Assumed knowledge on:

Active knowledge of statistics from high school (Dutch A-level math), or MAT-15303 Statistics 1.

### Continuation courses:

Note: This course can not be combined in an individual programme with MAT-14303 Basic Statistics.

MAT-20306 Advanced Statistics; MAT-22306 Quantitative Research Methodology and Statistics; MAT-24306 Advanced Statistics for Nutritionists.

### Contents:

Note: This course can not be combined in an individual programme with MAT-14303 Basic Statistics.

Building on an understanding of (simple) models, implications of model assumptions, interpretation of parameters; checking model assumptions; testing hypotheses for population means, for the 1-sample and 2-samples situations, for independent normal data (t-test); construction of a confidence interval for a population mean, or difference in means; simple linear regression and correlation, estimation, hypothesis testing and construction of a confidence interval for intercept, slope and predictions.
Ethical issues, as touching upon good statistical practice, will be discussed in class.

### Learning outcomes:

After successful completion of this course students are expected to be able to:
- comprehend basic ideas of the discussed methods;
- determine the appropriate statistical procedure, given the description of the experiment, the research question and the type of data;
- apply a hypothesis test for a (difference of) population mean(s), intercept or slope (t-test);
- construct a confidence interval for a (difference of) population mean(s), intercept, slope and predictions;
- show understanding of the implications of model assumptions;
- apply checks for model assumptions.

### Activities:

- tutorials that are motivated by practical problems from the Life Sciences, including making exercises;
- and (compulsory) computer practicals, analysing practical data with statistical software;
- prepare and hand in a brief report on a case study.

### Examination:

- open book examination consisting of multiple choice questions.
- the computer practical (attendance compulsory) has to result in a pass.
Successful partial interim examinations remain valid for a period of 2 years.

### Literature:

R. Lyman Ott; Michael Longnecker. (2013). An introduction to statistical methods and data analysis. 7th edition, ISBN-13: 978-1-305-26947-7 (6th edition may also be used).
Lecture notes provide an introduction to tutorials, exercises, and a reading guide for the book and the computer practicals. Available at the WUR-shop.

Programme Phase Specialization Period BBC Management and Consumer Studies BSc 1MO BBI Biology BSc 6AF BBT Biotechnology BSc 3AF BSW Soil, Water, Atmosphere BSc 3MO BBN Forest and Nature Conservation BSc 5AF BAS Animal Sciences BSc 2AF BIN International Development Studies BSc 5AF BLP Landscape Architecture and Planning BSc 2MO BIL International Land and Water Management BSc 2AF BFT Food Technology BSc 3MO BES Environmental Sciences BSc 4MO BPW Plant Sciences BSc 2MO BAT Biosystems Engineering BSc 3AF BVG Nutrition and Health BSc 4AF BCL Communication and Life Sciences BSc 5AF BGM Health and Society BSc 5AF BEB Economics and Governance BSc 1MO