MAT-15403 Statistics 2


Credits 3.00

Teaching methodContact hours
Independent study0
Course coordinator(s)dr. ir. EPJ Boer
dr ir NA Hartemink
Lecturer(s)G Mooiweer
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

Language of instruction:

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.


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.


- 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.


- 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.


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.

Compulsory for: BBCManagement and Consumer StudiesBSc1MO
BSWSoil, Water, AtmosphereBSc3MO
BBNForest and Nature ConservationBSc5AF
BASAnimal SciencesBSc2AF
BINInternational Development StudiesBSc5AF
BLPLandscape Architecture and PlanningBSc2MO
BILInternational Land and Water ManagementBSc2AF
BFTFood TechnologyBSc3MO
BESEnvironmental SciencesBSc4MO
BPWPlant SciencesBSc2MO
BATBiosystems EngineeringBSc3AF
BVGNutrition and HealthBSc4AF
BCLCommunication and Life SciencesBSc5AF
BGMHealth and SocietyBSc5AF
BEBEconomics and GovernanceBSc1MO