## Agenda

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Probability Theory

Probability axioms - Probability space Sample space - Elementary event - Random variable - Probability measure - Complementary event - Joint probability - Marginal probability - Conditional probability - Independence - Conditional independence - Law of total probability - Law of large numbers - Bayes' theorem - Venn diagram - Tree diagram

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Probability Distributions

Introduction: Probability mass function, Probability density function, Probability distribution function - Discrete univariate distributions: Binomial, Poisson, Geometric, Hypergeometric - Continuous univariate distributions: Uniform, Exponential, Normal (Gaussian)

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Frequentist Inference

Unbiased estimators (Mean unbiased minimum variance, Median unbiased) - Confidence interval - Testing hypotheses - Alpha-/Beta-Error and Power

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Specific Tests

Z (normal) - Student's t-test - F - Goodness of fit (Chi-squared) - Signed-rank (1-sample, 2-sample, 1-way anova)

## Trainer

Marco Skulschus (born in Germany in 1978) studied economics in Wuppertal (Germany) and Paris (France) and wrote his master´s thesis about semantic data modeling. He started working as a lecturer and consultant in 2002.

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Publications

- Grundlagen empirische Sozialforschung ISBN 978-3-939701-23-1
- System und Systematik von Fragebögen ISBN 978-3-939701-26-2
- Oracle PL/SQL ISBN 978-3-939701-40-8
- MS SQL Server - T-SQL Programmierung und Abfragen ISBN 978-3-939701-69-9

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Projects

- He works as an IT-consultant and project manager. He developed various Business Intelligence systems for industry clients and the public sector. For several years now, he is responsible for a BI-team in India which is mainly involved in BI and OLAP projects, reporting systems as well as statistical analysis and Data Mining.

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Research

He led several research projects and was leading scientist and project manager of a publicly funded project about interactive questionnaires and online surveys.