MAT-15403 Statistics 2

Course

Credits 3.00

Teaching methodContact hours
Practical intensively supervised12
Tutorial25
Self-study
Course coordinator(s)dr. ir. EPJ Boer
drs. H Engel
dr. EJH Korendijk
Lecturer(s)dr. ir. EPJ Boer
drs. H Engel
prof. dr. ir. J Grasman
ir. SLGE Burgers
dr. WT Kruijer
T Boot
drs. LCP Keizer
WJ Buist
AM Wubs
dr. EJH Korendijk
dr. LMW Akkermans
JFM Korstanje
dr. ing. M Knotters
ir. PFG Vereijken
dr. G Gort
MSc R Jacobs
dr. ing. MPH Verouden
KM Brolsma
dr. N van der Hoeven
dr. ing. A Pielaat
dr. C Dobre
dr. SK Schnabel
Examiner(s)dr. ir. EPJ Boer
drs. H Engel

Language of instruction:

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.

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 practical's, 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.

Literature:

R. Lyman Ott; Michael Longnecker. (2013). An introduction to statistical methods and data analysis. 6th ed. ISBN-13: 978-0-495-10914-3.
Lecture notes provide an introduction to tutorials, exercises, and a reading guide for the book and the computer practical's. Available: WUR-shop.

ProgrammePhaseSpecializationPeriod
Compulsory for: BBCManagement and Consumer StudiesBSc6MO
BBIBiologyBSc3MO
BBTBiotechnologyBSc3MO
BSWSoil, Water, AtmosphereBSc3AF
BBNForest and Nature ConservationBSc2MO
BASAnimal SciencesBSc5MO
BINInternational Development StudiesBSc5AF
BLPLandscape Architecture and PlanningBSc2AF
BILInternational Land and Water ManagementBSc2AF
BFTFood TechnologyBSc1MO
BESEnvironmental SciencesBSc4AF
BPWPlant SciencesBSc2MO
BATBiosystems EngineeringBSc3AF
BVGNutrition and HealthBSc4AF
BCLCommunication and Life SciencesBSc5AF
BGMHealth and SocietyBSc5AF
BEBEconomics and GovernanceBSc1MO
Restricted Optional for: MFNForest and Nature ConservationMSc2AF, 2MO