Statistics

• Dauer:
  3 Tage
• Zeit:
  10:00 - 16:00
• Lieferart:
  Online
• Zielgruppe:
  Information Workers
• Vorkenntnisse:
  General knowledge of math
• Methode:
  Lecture with examples and exercises.
• Erfahren Sie in der Demo mehr darüber, wie Online-Kurse durchgeführt werden.
• Kursnummer:
  2023246
• 
  Themen:
  In statistics, statistical inference is the process of drawing conclusions from data that is subject to random variation, for example, observational errors or sampling variation. Statistical induction helps describing systems of procedures that can be used to draw conclusions from datasets arising from systems affected by random variation, such as observational errors, random sampling, or random experimentation. It is then used to test hypotheses and make estimations using sample data. This training covers all the fundamentals of inductive statistics (probability theory, probability distributions and hypotheses testing) which can be used in marketing, controlling and engineering. You will learn theory and the mathematical foundations in lectures with examples and you will train your new knowledge in practical hands-on labs and exercices.

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

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

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

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

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.

Veröffentlichungen

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

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

Projekte: - 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.

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

Zertifizierung: Marco Skulschus is "Microsoft Certified Trainer", “Oracle Associate” and passed the ComptiaCTT+ examination.

Bei der Anmeldung von mehreren Teilnehmern bieten wir Ihnen attraktive Rabatte an. Ab drei Teilnehmern kann sich ein Inhouse-Seminar bei Ihnen lohnen. Gern erstellen wir Ihnen ein individuelles Angebot.
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