Autumn Semester 2020 takes place in a mixed form of online and classroom teaching.
Please read the published information on the individual courses carefully.

406-0603-AAL  Stochastics (Probability and Statistics)

SemesterAutumn Semester 2016
LecturersM. Kalisch
Periodicityevery semester recurring course
Language of instructionEnglish
CommentEnrolment ONLY for MSc students with a decree declaring this course unit as an additional admission requirement.

Any other students (e.g. incoming exchange students, doctoral students) CANNOT enrol for this course unit.



Catalogue data

AbstractIntroduction to basic methods and fundamental concepts of statistics and probability theory for non-mathematicians. The concepts are presented on the basis of some descriptive examples. Learning the statistical program R for applying the acquired concepts will be a central theme.
ObjectiveThe 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".
ContentFrom "Statistics for research" (online)
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

From "Introductory Statistics with R (online)"
Ch 1: Basics
Ch 2: The R Environment
Ch 3: Probability and distributions
Ch 4: Descriptive statistics and tables
Ch 5: One- and two-sample tests
Ch 6: Regression and correlation
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/

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits4 credits
ExaminersM. Kalisch
Typegraded semester performance
Language of examinationEnglish
RepetitionRepetition possible without re-enrolling for the course unit.

Learning materials

No public learning materials available.
Only public learning materials are listed.

Courses

NumberTitleHoursLecturers
406-0603-AA RStochastics (Probability and Statistics)
Self-study course. No presence required.
120s hrsM. Kalisch

Groups

No information on groups available.

Restrictions

There are no additional restrictions for the registration.

Offered in

ProgrammeSectionType
Computational Biology and Bioinformatics MasterCourse Units for Additional Admission RequirementsE-Information
Earth Sciences MasterCourse Units for Additional Admission RequirementsE-Information
Geomatic Engineering MasterCourse Units for Additional Admission RequirementsE-Information
Food Science MasterCourse Units for Additional Admission RequirementsE-Information
Medicinal and Industrial Pharmaceutical Sciences MasterCourse Units for Additional Admission RequirementsE-Information
Pharmaceutical Sciences MasterCourse Units for Additional Admission RequirementsE-Information
Spatial Development and Infrastructure Systems MasterCourse Units for Additional Admission RequirementsE-Information
Computational Science and Engineering MasterCourse Units for Additional Admission RequirementsE-Information
Environmental Sciences MasterCourse Units for Additional Admission RequirementsE-Information