SoSe 21: Statistical Methods for Small Sample Sizes
Frank Konietschke
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In this course, we introduce and discuss statistical inference methods for analyzing trials with small sample sizes. We hereby explore the impact of the standard assumption “N is large” ... read more
In this course, we introduce and discuss statistical inference methods for analyzing trials with small sample sizes. We hereby explore the impact of the standard assumption “N is large” and try to find an answer to the question “what means large?” The inference methods will cover estimation of treatment effects, confidence interval computations and hypothesis testing in both parametric and nonparametric models. Rank tests, bootstrap and permutation methods will be investigated in detail as approximation methods. This class aspires to learn about modern statistical tools that were designed to make accurate conclusions when sample sizes are rather small.
Course Material will be provided via Blackboard (lms.fu-berlin.de). In case of No face-to-face events the calss will also be held via Blackboard
