Aims
To teach students how to design and analyse experiments for ecological and evolutionary studies. To prepare students for future and ongoing thesis projects.
Content
Students from all fields of ecology and evolutionary biology are invited to attend as these methods are needed in all experimental sciences. The course will consist of a mixture of lectures, tutorials and extensive assignments. Lecture topics include ANOVA, regression and categorical data analysis. As time permits, spatial analysis, autocorrelation and Monte Carlo techniques will be included. Tutorials will include the management and documentation of data and the use of statistical packages (SPSS, JMP and Excel). The focus will be on performing and evaluating analyses on datasets from ongoing experiments in ecology and evolutionary biology. Students are required to bring datasets with them, preferably from their own work in progress. The course and all written assignments will be in English.
Schedule
Class time will be divided into lectures and totorial sessions. some tutorial sessions will be in small groups of students.
Prerequisites
Only basic knowledge of statistics is required and a desire to know what your data says! Preference will be given to Ph.D. students but other students are invited to apply with further preference given to those currently working on research projects.
Credits
10 ECTS credits for completion of all assignments during the course period. Additional 5 ECTS credits can be obtained for successful completion of research paper or grant proposal based on student's current work to be done within 3 months of the course.
Examination
3 written assignments, 1 oral presentation required for 10 ECTS credits. These plus a final paper/grant proposal for 15 ECTS.
No. of participants
Limited to 12.
Materials
ONE of either of the following text books made be used with the course.
1. 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. (This is a set of two books and should be purchased together)
2. Zar, JH. (1999). Biostatistical Analysis. 4th edition. Prentice Hall, NJ, USA.
Original journal articles. A list will be provided to applicants.
Access to a computer with spreadsheet, statistics and graphics software. Instructions for use of SPSS, JMP and Excel shall be provided but students may use any statistical package that includes mulitvariate analyses. Students are responsible for obtaining access to computers and software.
Lecturer
NN