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Stochastics (Probability and Statistics)
Last Updated: 2026-06-03 00:13:58
Abstract
Introduction to basic methods and fundamental concepts of statistics andprobability theory for non-mathematicians. The concepts are presented onthe basis of some descriptive examples. The course will be based on thebook "Statistics for research" by S. Dowdy et.al. and on thebook "Introductory Statistics with R" by P. Dalgaard.
Objective
The objective of this course is to build a solid fundament in probability and statistics. The student should understand some fundamental concepts and be able to apply these concepts to applications in the real world. Furthermore, the student should have a basic knowledge of the statistical programming language "R". The main topics of the course are: - Introduction to probability - Common distributions - Binomialtest - z-Test, t-Test - Regression
Content
From "Statistics for research": Ch 1: The Role of Statistics Ch 2: Populations, Samples, and Probability Distributions Ch 3: Binomial Distributions Ch 6: Sampling Distribution of Averages Ch 7: Normal Distributions Ch 8: Student's t Distribution Ch 9: Distributions of Two Variables [Regression] From "Introductory Statistics with R": Ch 1: Basics Ch 2: Probability and distributions Ch 3: Descriptive statistics and tables Ch 4: One- and two-sample tests Ch 5: Regression and correlation
Resources
Literature
"Statistics for research" by S. Dowdy et. al. (3rd edition); Print ISBN: 9780471267355; Online ISBN: 9780471477433; DOI: 10.1002/0471477435; From within the ETH, this book is freely available online under: http://onlinelibrary.wiley.com/book/10.1002/0471477435 "Introductory Statistics with R" by Peter Dalgaard; ISBN 978-0-387-79053-4; DOI: 10.1007/978-0-387-79054-1 From within the ETH, this book is freely available online under: http://www.springerlink.com/content/m17578/
General Information
- Language
- English
- Levels
- MSC
- Frequency
- Semesterly recurring
Examination
- Type
- graded semester performance
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| revision course / private study |
Stochastics (Probability and Statistics)
Self-study course. No presence required.
|
No time listed | 120 h semesterly |
Offered In
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Course Units for Additional Admission Requirements (The courses below are only available for MSc students with additional admission requirements.)
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Course Units for Additional Admission Requirements (The courses below are only available for MSc students with additional admission requirements.)
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Course Units for Additional Admission Requirements (The courses below are only available for MSc students with additional admission requirements.)
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Course Units for Additional Admission Requirements (The courses below are only available for MSc students with additional admission requirements.)
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Course Units for Additional Admission Requirements (The courses below are only available for MSc students with additional admission requirements.)
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Course Units for Additional Admission Requirements (The courses below are only available for MSc students with additional admission requirements.)
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Computational Biology and Bioinformatics Master (More informations at: )
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Course Units for Additional Admission Requirements (The courses below are only available for MSc students with additional admission requirements.)
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Statistics Master (The following courses belong to the curriculum of the Master's Programme in Statistics. The corresponding credits do not count as external credits even for course units where an enrolment at ETH Zurich is not possible.)
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Course Units for Additional Admission Requirements (The courses below are only available for MSc students with additional admission requirements.)
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Course Units for Additional Admission Requirements (The courses below are only available for MSc students with additional admission requirements.)
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Course Units for Additional Admission Requirements (The courses below are only available for MSc students with additional admission requirements.)
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