# MAT-15403 Statistics 2

## Course

Credits 3.00

 Teaching method Contact hours Tutorial 26 Practical 12 Independent study
 Course coordinator(s) dr. ir. EPJ Boer drs. H Engel dr. EJH Korendijk Lecturer(s) SF Westerink dr DJ Brus ir. W van den Berg J van den Boom NGWM van Strijp-Lockefeer dr ir NA Hartemink MSc RM Hu dr. ir. EPJ Boer drs. H Engel ir. SLGE Burgers drs. LCP Keizer MSc V Emonds G Mooiweer dr. EJH Korendijk dr. LMW Akkermans dr. ing. M Knotters dr. ing. MPH Verouden NJ Vendrig dr. C Dobre dr. SK Schnabel Examiner(s) dr. ir. EPJ Boer drs. H Engel

Dutch

### Assumed knowledge on:

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

### Continuation courses:

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

### Contents:

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 this course, the student is 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.
- CAS: yes;
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: WUR-shop.

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