Admission requirements
Linear Models
Recommended: Essentials of Mixed and Longitudinal Modelling
Description
A good study design is important because poorly designed studies will produce imprecise and biased results. Furthermore, an experiment with plants or animals that doesn't produce significant results is a waste of time, money and resources. From a statistical point of view, a statistical design addresses the choice of treatments and how to deal with disturbing factors and sources of random variation. The statistical principles underlying experimental designs can be summarized by randomization, replication and blocking. In this course, you will learn about the most common designs for biological and agricultural experiments and how to analyze them. Further, you will learn about criteria and strategies for choosing treatments and experimental designs.
Course Objectives
The objectives for this course are as follows:
Identify the structural characteristics of common agricultural and biological experimental designs and propose adequate linear and linear mixed models for their analysis: completely randomized design, randomized complete block design, incomplete block design, Latin square design, split plot design, fractional factorial design, response surface design
Know common treatment designs (contrasts, factorial, crossed, nested)
Choose and motivate a suitable experimental and treatment design for a particular situation
Define relevant treatment contrasts and corresponding standard errors as functions of experimental design and replication
Define ANOVA and mixed models corresponding to experimental and treatment designs, perform calculations and interpret results
Know about intra and inter block variation and recovery of inter block information
Know how to deal with unbalanced data
Derive expected mean squares for common designs and corresponding F-tests for treatment differences
Know how to make power calculations for different designs
Timetable
You will find the timetables for all courses and degree programmes of Leiden University in the tool MyTimetable (login). Any teaching activities that you have sucessfully registered for in MyStudyMap will automatically be displayed in MyTimeTable. Any timetables that you add manually, will be saved and automatically displayed the next time you sign in.
MyTimetable allows you to integrate your timetable with your calendar apps such as Outlook, Google Calendar, Apple Calendar and other calendar apps on your smartphone. Any timetable changes will be automatically synced with your calendar. If you wish, you can also receive an email notification of the change. You can turn notifications on in ‘Settings’ (after login).
For more information, watch the video or go the the 'help-page' in MyTimetable. Please note: Joint Degree students Leiden/Delft have to merge their two different timetables into one. This video explains how to do this.
Mode of Instruction
Lectures and discussion of exercises, homework and assignments
Assesment method
Written Exam, plus a limited number of mandatory assignments, which will be graded The final grade will consist of 1/3 x the grade for the assignments + 2/3 the grade for the written exam.
Reading list
Welham SJ, Gezan SA, Clark SJ, Mead A. Statistical Methods in Biology: Design and Analysis of Experiments and Regression. Chapman and Hall/CRC. 2014
Registration
From the academic year 2022-2023 on every student has to register for courses with the new enrollment tool MyStudyMap. There are two registration periods per year: registration for the fall semester opens in July and registration for the spring semester opens in December. Please see this page for more information.
Please note that it is compulsory to both preregister and confirm your participation for every exam and retake. Not being registered for a course means that you are not allowed to participate in the final exam of the course. Confirming your exam participation is possible until ten days before the exam.
Extensive FAQ's on MyStudymap can be found here.
Contact
Fred van Eeuwijk: fred.vaneeuwijk@wur.nl
Gerrit Gort: gerrit.gort@wur.nl