MAT-20306 Advanced Statistics

Course

Credits 6.00

Teaching methodContact hours
Lecture24
Tutorial18
Practical24
Independent study0
Course coordinator(s)dr. EJ Bakker
Lecturer(s)prof. dr. FA van Eeuwijk
ir. SLGE Burgers
dr. ir. E Heuvelink
dr. EJ Bakker
dr. G Gort
dr. B Engel
dr DJ Brus
SE Wilson
G Korontzis
dr. WT Kruijer
dr. SK Schnabel
drs. LCP Keizer
dr. LMW Akkermans
dr. EJH Korendijk
S Gugushvile
V Avagyan
dr. JA Hageman
drs CGF de Kovel
Examiner(s)dr. EJ Bakker
dr. G Gort

Language of instruction:

English

Assumed knowledge on:

MAT-15303 Statistics 1 + MAT-15403 Statistics 2 or MAT-14303 Basic Statistics or MAT-15403 Statistics 2.
The student should be familiar with 1) The principles of probability calculus and the subjects: estimation, construction of confidence intervals and hypothesis testing from statistical inference 2) Application of these principles to inference about central values (mean or success probability) for the 1-sample and 2-sample situations, in case of Normal observations and binary (0,1) observations 3) Methods of analysis for simple (one explanatory variable) linear regression.
(To refresh this knowledge, (parts of) chapters 1 to 6 and 11 of the book can be studied.)

Contents:

Note: This course can not be combined in an individual programme with MAT-24306 Advanced Statistics for Nutritionists and/or MAT-25303 Advanced Statistics (DL).

Per week we will have 2 lectures of two hours each (for groups up to 120 students) 2 computer practicals of two hours each (for groups of 20 students with 2 teachers / 1 teacher with one student assistant) and one T16 tutorial (of 3 hours) where students will do exercises with pen and paper (max 32 students supervised by 1 teacher and 1 student assistant).

Learning outcomes:

After successful completion of this course students are expected to (within the limits of the subjects treated) be able to:
- translate a research question into a statistical hypothesis: make a plan (type of design or sampling procedure) for the data collection.
- choose an appropriate model with an understanding of the ingredients of the model in relation to the data;
- analyse the data (with SPSS and R);
- interpret the results and form conclusions relevant for the actual problem.

Activities:

- lectures: follow classes;
- study the book and make exercises;
- computer practicals (compulsory): (learn how to) use SPSS, R and PQRS, and work on case studies;
- pen and paper practicals: work on exercises and case studies where computer output is given.

Examination:

- written test with open questions and multiple choice questions, which needs to be passed (contribution to final mark: 100%).
- computer practical (attendance compulsory) has to result in a pass.

Literature:

R. Lyman Ott; Longnecker, M.T. (2016). An Introduction to Statistical Methods and Data Analysis. 7th ed. 1174p.
Lecture notes available in English. (available at the WUR-shop).

ProgrammePhaseSpecializationPeriod
Compulsory for: BASAnimal SciencesBSc1MO, 1AF, 2MO, 2AF, 5MO, 6MO
BPWPlant SciencesBSc1MO, 1AF, 2MO, 2AF, 5MO, 6MO
BEBEconomics and GovernanceBSc6MO
MAMAquaculture and Marine Resource ManagementMSc2MO, 5MO, 6MO
Restricted Optional for: BINInternational Development StudiesBScB: Economics of Development5MO
MBIBiologyMSc1AF, 1MO, 2AF, 2MO, 5MO, 6MO
MOAOrganic AgricultureMSc1MO, 1AF, 5MO, 6MO
MOAOrganic AgricultureMScC: Double Degree Agroecology1MO, 2MO, 5MO
MASAnimal SciencesMSc1MO, 1AF, 2MO, 2AF, 5MO, 6MO
MFTFood TechnologyMScG: Sensory Science1MO
MESEnvironmental SciencesMSc2AF, 5MO
MPSPlant SciencesMScC: Natural Resource Management1MO, 2MO, 5MO, 6MO
MPSPlant SciencesMScD: Plant Breeding and Genetic Resources1MO, 2MO, 5MO, 6MO
MPBPlant BiotechnologyMSc1MO, 1AF, 2MO, 2AF, 5MO, 6MO
MNHNutrition and HealthMScA: Nutritional and Public Health Epidemiology1MO, 1AF
MNHNutrition and HealthMScD: Sensory Science1MO, 1AF
MNHNutrition and HealthMScB: Nutritional Physiology and Health Status1MO, 1AF
MNHNutrition and HealthMScF: Food Digestion and Health1MO, 1AF
MNHNutrition and HealthMScC: Molecular Nutrition and Toxicology1MO, 1AF
MBFBioinformaticsMSc1AF, 2AF, 6MO
MIDInternational Development StudiesMScB: Economics of Development1AF
MFQFood Quality ManagementMSc1AF, 6MO
MBSBiobased SciencesMScC: Biobased and Circular Economy2AF, 2MO, 5MO, 6MO