Modern statistics in natural science, 5 credits
Modern statistik i naturvetenskaper
Language of instruction: English
Course period: Part time during late January – mid-March 2022.
Campus teaching or online teaching: The course is planned to run on campus 2022, but can be switched to online if restrictions makes this impossible.
Basic statistical knowledge.
To give an introduction to the most commonly applied modern statistical techniques and tools used in a wide range of natural sciences. In addition to providing an overview of the statistical “tool-box”, the course generates an understanding of the philosophy and reasoning behind statistical design, modelling and inference. Practical elements (exercises) and group discussions gives the students hands-on experience, deeper insights and confidence. This is a general course in applied statistics that attracts PhD students from biology, geosciences, chemistry, information technology, experimental physics and related fields.
LEARNING OUTCOMES FOR DOCTORAL DEGREE
The course develops and discusses a number of fundamental and general goals in postgraduate education, such as scientific inferences, limitations of dualism, hypothesis testing, scientific transparency, good statistical practice, experimental design and numerical analysis. More specific goals include insights into choice, and execution, of statistical models and interpretation of statistical analysis.
The course is focused on analyses of experimental data, but observational data analyses are also covered briefly. The course includes: experimental designs leading to ANOVA or ANCOVA, including block experiments, repeated measurement designs, nested and factorial designs, multiple regression including strategies for selecting variables and evaluating models, generalized linear models (GLIM) including logistic and Poisson regression, contingency table tests, power analysis, multivariate analysis and ordination techniques, resampling and permutation statistics, Bayesian model fitting, MCMC techniques, geometric morphometrics and a few other topics.
The core of the course is built around a series of 13 half-day and interactive lectures. In addition, the students then work off-schedule with a series of common practical elements/problems that are then discussed during a series of tutored group discussions. Hands-on advice and individual tutoring of the use of statistical software (R) is also offered at several occasions during the course.
Attendance at all lectures and approved individual practical reports that students hand in.
Göran Arnqvist, Goran.Arnqvist@ebc.uu.se
DEPARTMENT WITH MAIN RESPONSIBILITY
Department of Ecology and Genetics
Submit the application for admission to: https://forms.gle/PfaeBRfum7UF8eJi8
Submit the application not later than: 2021-12-31