Aims
To teach students how to design and analyse experiments in ecology, evolution, and other areas of biology. To prepare students for future and ongoing thesis projects.
Content
A mixture of lectures and extensive assignments to be completed during laboratory hours or more as needed. The laboratoty periods will be used to learn the use of software and perform analyses. The course is divided in a 2 credit segment on topics related mainly to the textbook (ANOVA, regression, correlation, loglinear analysis), and a 1 credit segment on experimental design, multivariate statistics, spatial analysis and Monte Carlo approaches. The focus will be on the application and evaluation of statistics to typical ecological experiments. Students are encouraged to bring data from their own thesis projects but other datasets will be provided for use in all assignments if needed. Though most examples will be drawn from botanical studies, students with other interests are invited to attend.
Teaching curriculum: 4 Lectures (2x2) and 6 hours of laboratory exercises weekly for 12 weeks. The entire course including all written assignments will be in English.
Prerequisites: Basic knowledge of statistics is required. The course is aimed at Ph.D. students. In case of vacancy, graduate students will only be invited to participate if they are currently working on thesis research projects. Students MUST contact the instructor via email before attending the course. The availability of space and the status of student's research are important criteria for participation.
Teacher: Pamela Hall, Pamela.Hall@biology.aau.dk
Limit on number of attendees: 12
Teaching material: Articles from current literature : packet supplied by instructor.
Evaluation
No final exam will be given but students must complete all assignments, do an oral presentation and a write final paper using their own data.
Text-book
One to be selected by instructor by July. The appropriate book will be available for purchase at the University book store.
Sokal, R.R. and Rohlf, F.J. 1995. Biometry (3rd edition) - W.H. Freeman and Company, New York, USA. Rohlf, F.J. and Sokal, R.R. 1995. Statistical Tables (3rd edition) - W.H. Freeman and Company, New York, USA.
OR
Zar, JH. 1999. Biostatistical Analysis (4th edition). Prentice Hall, London.
Students must have their own access to a computer and appropriate statistical software. Examples include : SPSS, SAS, Systat, Statistica, JMP etc. Excel is NOT sufficient.
ECTS-credits
15
Semester
Fall