MAT-15403 Statistics 2

Course

Credits 3.00

Teaching methodContact hours
Tutorial26
Practical12
Independent study0
Course coordinator(s)dr. ir. EPJ Boer
drs. H Engel
MSc RM Hu
Lecturer(s)ir. SLGE Burgers
dr. ing. M Knotters
dr. ir. EPJ Boer
drs. LCP Keizer
dr. ing. MPH Verouden
dr. C Dobre
drs. H Engel
dr. EJH Korendijk
dr. LMW Akkermans
dr. SK Schnabel
dr ir NA Hartemink
dr. ir. J van Heerwaarden
dr. CGF de Kovel
dr. EJ Bakker
dr DJ Brus
BJB Stout
V Avagyan
S Gugushvile
dr. P Behrouzi PhD
G Mooiweer
MSc RM Hu
J van den Boom
AP Languillaume
NGWM van Strijp-Lockefeer
Examiner(s)drs. H Engel
dr. ir. EPJ Boer

Language of instruction:

Spoken language Dutch or English (depending on the study program), all written materials in English, examination in English

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 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.
- 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.

ProgrammePhaseSpecializationPeriod
Compulsory for: BBCManagement and Consumer StudiesBSc1MO
BBIBiologyBSc6WD
BBTBiotechnologyBSc3AF
BSWSoil, Water, AtmosphereBSc3MO
BBNForest and Nature ConservationBSc5AF
BASAnimal SciencesBSc5AF
BINInternational Development StudiesBSc5AF
BLPLandscape Architecture and PlanningBSc2AF
BILInternational Land and Water ManagementBSc2AF
BFTFood TechnologyBSc3MO
BESEnvironmental SciencesBSc4MO
BPWPlant SciencesBSc2AF
BATBiosystems EngineeringBSc4AF
BVGNutrition and HealthBSc4AF
BCLCommunication and Life SciencesBSc5AF
BGMHealth and SocietyBSc5AF
Restricted Optional for: MFNForest and Nature ConservationMSc2AF