Search result: Catalogue data in Spring Semester 2021

Statistics Master Information
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.
GESS Science in Perspective
Two credits are needed from the "Science in Perspective" programme with language courses excluded if three credits from language courses have already been recognised for the Bachelor's degree.
see Link (Eight credits must be acquired in this category: normally six during the Bachelor’s degree programme, and two during the Master’s degree programme. A maximum of three credits from language courses from the range of the Language Center of the University of Zurich and ETH Zurich may be recognised. In addition, only advanced courses (level B2 upwards) in the European languages English, French, Italian and Spanish are recognised. German language courses are recognised from level C2 upwards.)
» see Science in Perspective: Type A: Enhancement of Reflection Capability
» Recommended Science in Perspective (Type B) for D-MATH
» see Science in Perspective: Language Courses ETH/UZH
Master's Thesis
NumberTitleTypeECTSHoursLecturers
401-2000-00LScientific Works in Mathematics
Target audience:
Third year Bachelor students;
Master students who cannot document to have received an adequate training in working scientifically.
O0 creditsM. Burger
AbstractIntroduction to scientific writing for students with focus on publication standards and ethical issues, especially in the case of citations (references to works of others.)
ObjectiveLearn the basic standards of scientific works in mathematics.
Content- Types of mathematical works
- Publication standards in pure and applied mathematics
- Data handling
- Ethical issues
- Citation guidelines
Lecture notesMoodle of the Mathematics Library: Link
Prerequisites / NoticeDirective Link
401-2000-01LLunch Sessions – Thesis Basics for Mathematics Students
Details and registration for the optional MathBib training course: Link
Z0 creditsSpeakers
AbstractOptional course "Recherchieren in der Mathematik" (held in German) by the Mathematics Library.
Objective
401-4990-02LMaster's Thesis Restricted registration - show details
Only students who fulfil the following criteria are allowed to begin with their Master's thesis:
a. successful completion of the Bachelor's programme;
b. fulfilling of any additional requirements necessary to gain admission to the Master's programme;
c. They have acquired at least 16 credits in the category “Core courses” for Programme Regulations 2014 and 40 credits in the category “Main Areas” for Programme Regulations 2020.

Successful participation in the course unit 401-2000-00L Scientific Works in Mathematics is required.
For more information, see Link
O30 credits57DSupervisors
AbstractThe master's thesis concludes the study programme. Thesis work should prove the students' ability to independent, structured and scientific working.
ObjectiveDie Studierenden sollen mit der Master-Arbeit, die den Abschluss des Studiengangs bildet, ihre Fähigkeit zu selbständiger, strukturierter und wissenschaftlicher Tätigkeit unter Beweis stellen.
Course Units for Additional Admission Requirements
The courses below are only available for MSc students with additional admission requirements.
NumberTitleTypeECTSHoursLecturers
406-0173-AALLinear Algebra I and II
Enrolment 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.
E-6 credits13RN. Hungerbühler
AbstractLinear algebra is an indispensable tool of engineering mathematics. The course is an introduction to basic methods and fundamental concepts of linear algebra and its applications to engineering sciences.
ObjectiveAfter completion of this course, students are able to recognize linear structures and to apply adequate tools from linear algebra in order to solve corresponding problems from theory and applications. In addition, students have a basic knowledge of the software package Matlab.
ContentSystems of linear equations, Gaussian elimination, solution space, matrices, LR decomposition, determinants, structure of linear spaces, normed vector spaces, inner products, method of least squares, QR decomposition, introduction to MATLAB, applications.
Linear maps, kernel and image, coordinates and matrices, coordinate transformations, norm of a matrix, orthogonal matrices, eigenvalues and eigenvectors, algebraic and geometric multiplicity, eigenbasis, diagonalizable matrices, symmetric matrices, orthonormal basis, condition number, linear differential equations, Jordan decomposition, singular value decomposition, examples in MATLAB, applications.

Reading:

Gilbert Strang "Introduction to linear algebra", Wellesley-Cambridge Press: Chapters 1-6, 7.1-7.3, 8.1, 8.2, 8.6

A Practical Introduction to MATLAB: Link

Matlab Primer: Link
Literature- Gilbert Strang: Introduction to linear algebra. Wellesley-Cambridge Press

- A Practical Introduction to MATLAB: Link

- Matlab Primer: Link

- K. Nipp / D. Stoffer, Lineare Algebra, vdf Hochschulverlag, 5. Auflage 2002

- K. Meyberg / P. Vachenauer, Höhere Mathematik 1, Springer 2003
406-0243-AALAnalysis I and II Information
Enrolment 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.
E-14 credits30RM. Akveld
AbstractMathematical tools for the engineer
ObjectiveMathematics as a tool to solve engineering problems. Mathematical formulation of technical and scientific problems. Basic mathematical knowledge for engineers.
ContentShort introduction to mathematical logic.
Complex numbers.
Calculus for functions of one variable with applications.
Simple types of ordinary differential equations.
Simple Mathematical models in engineering.

Multi variable calculus: gradient, directional derivative, chain rule, Taylor expansion. Multiple integrals: coordinate transformations, path integrals, integrals over surfaces, divergence theorem, applications in physics.
LiteratureTextbooks in English:
- J. Stewart: Calculus, Cengage Learning, 2009, ISBN 978-0-538-73365-6
- J. Stewart: Multivariable Calculus, Thomson Brooks/Cole (e.g. Appendix G on complex numbers)
- V. I. Smirnov: A course of higher mathematics. Vol. II. Advanced calculus
- W. L. Briggs, L. Cochran: Calculus: Early Transcendentals: International Edition, Pearson Education
Textbooks in German:
- M. Akveld, R. Sperb: Analysis I, vdf
- M. Akveld, R. Sperb: Analysis II, vdf
- L. Papula: Mathematik für Ingenieure und Naturwissenschaftler, Vieweg Verlag
- L. Papula: Mathematik für Ingenieure 2, Vieweg Verlag
406-0603-AALStochastics (Probability and Statistics)
Enrolment 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.
E-4 credits9RM. Kalisch
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. The course will be based on the
book "Statistics for research" by S. Dowdy et.al. and on the
book "Introductory Statistics with R" by P. Dalgaard.
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". The main topics of the course are:
- Introduction to probability
- Common distributions
- Binomialtest
- z-Test, t-Test
- Regression
ContentFrom "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
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:
Link

"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:
Link
406-2604-AALProbability and Statistics
Enrolment 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.
E-7 credits15RJ. Teichmann
Abstract- Statistical models
- Methods of moments
- Maximum likelihood estimation
- Hypothesis testing
- Confidence intervals
- Introductory Bayesian statistics
- Linear regression model
- Rudiments of high-dimensional statistics
ObjectiveThe goal of this part of the course is to provide a solid introduction into statistics. It offers of a wide overview of the main tools used in statistical inference. The course will start with an introduction to statistical models and end with some notions of high-dimensional statistics. Some time will be spent on proving certain important results. Tools from probability and measure theory will be assumed to be known and hence will be only and occasionally recalled.
Lecture notesScript of Prof. Dr. S. van de Geer
LiteratureThese references could be use complementary sources:

R. Berger and G. Casella, Statistical Inference
J. A. Rice, Mathematical Statistics and Data Analysis
L. Wasserman, All of Statistics
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