This course teaches you how to discern and discuss basic statistical concepts: independent observations, ordinary least squares, maximum likelihood, generalised linear models, analysis of variance/deviance and error distributions, as well as to explain the importance of independent observations in sampling data for statistical analysis. You will also learn how to describe the ideas of significance testing by comparing variance explained to random variance, as well as to independently report standard descriptive measurements and construct and interpret generalised linear models with normal and binomial error distributions. In addition, you will examine and explain the limitations of statistical results; are they globally valid or only valid for the specific experimental set-ups, to which population do they refer, how could confounding (not measured) variables explain the results?
The course is taught through lectures, practical exercises, computer-based exercises and seminars. You can also participate in guest lectures and research seminars. Grades are awarded on basis of continual assessment through hand-in assignments.