Workshop: GOOD (AND NOT SO GOOD) STATISTICAL PRACTICE COMMON ERRORS IN QUANTITATIVE RESEARCH AND HOW TO AVOID THEM
Publication date: 08-02-2018 13:45
Workshop, February 15-16 Peter Pütz and Bruno de Sousa
The course will cover basic (but often misunderstood) statistical concepts from a rather practical and less mathematical perspective. Questions such as "What can we learn from data?" and "How much can we trust our results and the results of other researchers?" will be addressed. Also planned for this course are the more specific topics of random variables, properties of statistical estimators, statistical inference (confidence intervals, p-values, power), publication bias, pre-registration, p-hacking and Bayesian thinking. Although discussion of these topics may seem unnecessary for more or less experienced researchers, there have indeed been recent and rather intensive debates in the literature about such issues. Thus, the course is intended to provide very relevant recommendations for empirical research. An introduction to the software R as well as hands-on exercises in R will also be an integral part of the course. No prior knowledge in R is expected. The course will be given in English.