Search result: Courses in Spring Semester 2019

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.
Core Courses
In each subject area, the core courses offered are normally mathematical as well as application-oriented in content. For each subject area, only one of these is recognised for the Master degree.
Regression
NumberTitleTypeECTSHoursLecturers
401-3622-00LRegressionW8 credits4G
401-3622-00 GRegression
Does not take place this semester.
planned to be offered in the Autumn Semester 2019 as a yearly recurring course with new course title: Statistical Modelling
4 hrsnot available
Analysis of Variance and Design of Experiments
No offering in this semester yet
Multivariate Statistics
NumberTitleTypeECTSHoursLecturers
401-6102-00LMultivariate StatisticsW4 credits2G
401-6102-00 GMultivariate Statistics2 hrs
Mon13:15-15:00HG D 1.1 »
18.02.13:15-15:00HG D 1.2 »
25.02.13:15-15:00HG D 1.2 »
N. Meinshausen
401-0102-00LApplied Multivariate StatisticsW5 credits2V + 1U
401-0102-00 VApplied Multivariate Statistics2 hrs
Mon15:15-17:00HG F 3 »
F. Sigrist
401-0102-00 UApplied Multivariate Statistics
The exercise class originally scheduled on Monday, 15 April will take place on Friday, 12 April, 11-13 in HG D 7.1.
1 hrs
Mon/2w08:15-10:00HG D 1.1 »
12.04.11:15-13:00HG D 7.1 »
F. Sigrist
Time Series and Stochastic Processes
NumberTitleTypeECTSHoursLecturers
401-6624-11LApplied Time SeriesW5 credits2V + 1U
401-6624-11 VApplied Time Series2 hrs
Mon10:15-12:00HG E 1.2 »
M. Dettling
401-6624-11 UApplied Time Series1 hrs
Mon/2w08:15-10:00HG D 1.1 »
M. Dettling
Mathematical Statistics
No offering in this semester yet
Specialization Areas and Electives
Statistical and Mathematical Courses
NumberTitleTypeECTSHoursLecturers
401-4632-15LCausality Information W4 credits2G
401-4632-15 GCausality2 hrs
Wed10:15-12:00HG E 3 »
C. Heinze-Deml
401-3632-00LComputational StatisticsW8 credits3V + 1U
401-3632-00 VComputational Statistics
On 18 April 2019 the course takes place in HG E 3.
3 hrs
Thu13:15-15:00HG F 3 »
Fri09:15-10:00HG G 3 »
18.04.13:15-15:00HG E 3 »
M. H. Maathuis
401-3632-00 UComputational Statistics
A "Präsenzstunde" directly following the exercises will be offered Friday 11-12 in HG F 3.
1 hrs
Fri10:15-11:00HG F 3 »
M. H. Maathuis
401-3602-00LApplied Stochastic Processes Information W8 credits3V + 1U
401-3602-00 VApplied Stochastic Processes3 hrs
Tue10:15-12:00HG D 5.2 »
Wed13:15-14:00HG G 3 »
V. Tassion
401-3602-00 UApplied Stochastic Processes
Thu 9-10 or Thu 12-13
1 hrs
Thu09:15-10:00HG D 7.2 »
09:15-10:00HG F 26.3 »
12:15-13:00HG D 7.2 »
V. Tassion
401-3642-00LBrownian Motion and Stochastic Calculus Information W10 credits4V + 1U
401-3642-00 VBrownian Motion and Stochastic Calculus4 hrs
Wed08:15-10:00HG G 3 »
Thu10:15-12:00HG D 7.2 »
W. Werner
401-3642-00 UBrownian Motion and Stochastic Calculus
Fri 8-9, Fri 9-10 or Fri 12-13 depending on sufficient demand
1 hrs
Fri08:15-09:00HG D 3.2 »
08:15-09:00HG G 26.5 »
09:15-10:00HG D 3.2 »
09:15-10:00HG G 26.5 »
12:15-13:00HG D 5.2 »
12:15-13:00HG G 26.5 »
W. Werner
401-6228-00LProgramming with R for Reproducible Research Information W1 credit1G
401-6228-00 GProgramming with R for Reproducible Research14s hrs
Tue/114:15-16:00HG E 1.1 »
09.04.13:15-16:00LFW B 2 »
M. Mächler
401-4627-00LEmpirical Process Theory with Applications in Statistics and Machine Learning Information W4 credits2V
401-4627-00 VEmpirical Process Theory with Applications in Statistics and Machine Learning2 hrs
Thu08:15-10:00HG E 5 »
S. van de Geer
401-3629-00LQuantitative Risk ManagementW4 credits2V + 1U
401-3629-00 VQuantitative Risk Management2 hrs
Thu10:15-12:00ML H 44 »
P. Cheridito
401-3629-00 UQuantitative Risk Management1 hrs
Thu12:15-13:00ML H 44 »
P. Cheridito
401-4658-00LComputational Methods for Quantitative Finance: PDE Methods Information Restricted registration - show details W6 credits3V + 1U
401-4658-00 VComputational Methods for Quantitative Finance: PDE Methods
Permission from lecturers required for all students.
3 hrs
Wed13:15-15:00HG D 1.2 »
Fri14:15-15:00HG D 1.2 »
L. Herrmann, K. Kirchner
401-4658-00 UComputational Methods for Quantitative Finance: PDE Methods1 hrs
Fri13:15-14:00HG D 1.2 »
15:15-16:00HG D 1.2 »
L. Herrmann, K. Kirchner
401-2284-00LMeasure and Integration Information W6 credits3V + 2U
401-2284-00 VMass und Integral3 hrs
Tue08:15-09:00HG G 3 »
Thu08:15-10:00HG G 3 »
J. Teichmann
401-2284-00 UMass und Integral
Die Übungen finden Fr 10-12 statt. Als Ausweichtermin für Studierende, welche Elektrodynamik besuchen, ist Fr 14-16 vorgesehen.
2 hrs
Fri10:15-12:00CAB G 56 »
10:15-12:00CLA E 4 »
10:15-12:00LEE C 114 »
10:15-12:00LFW C 5 »
10:15-12:00ML F 40 »
14:15-16:00HG E 1.1 »
J. Teichmann
401-3903-11LGeometric Integer ProgrammingW6 credits2V + 1U
401-3903-11 VGeometric Integer Programming2 hrs
Thu13:15-15:00HG G 26.3 »
R. Weismantel, J. Paat, M. Schlöter
401-3903-11 UGeometric Integer Programming1 hrs
Wed12:15-13:00HG F 26.3 »
R. Weismantel, J. Paat, M. Schlöter
401-4904-00LCombinatorial Optimization Information W6 credits2V + 1U
401-4904-00 VCombinatorial Optimization
takes place in HG G 19.1 with the following exceptions: 21 February, 14 March and 21 March 2019 in HG D 1.2
2 hrs
Thu16:15-18:00HG D 1.2 »
16:15-18:00HG G 19.1 »
18.04.16:15-17:00HG D 1.2 »
16:15-17:00HG G 19.1 »
R. Zenklusen
401-4904-00 UCombinatorial Optimization
Starts in the second week of the semester.
1 hrs
Mon14:15-15:00HG E 1.2 »
R. Zenklusen
261-5110-00LOptimization for Data Science Information W8 credits3V + 2U + 2A
261-5110-00 VOptimization for Data Science3 hrs
Mon15:15-16:00HG E 1.1 »
Tue10:15-12:00ETF C 1 »
B. Gärtner, D. Steurer
261-5110-00 UOptimization for Data Science2 hrs
Tue13:15-15:00CHN G 22 »
13:15-15:00HG D 3.2 »
13:15-15:00RZ F 21 »
B. Gärtner, D. Steurer
261-5110-00 AOptimization for Data Science2 hrsB. Gärtner, D. Steurer
252-0526-00LStatistical Learning Theory Information W7 credits3V + 2U + 1A
252-0526-00 VStatistical Learning Theory3 hrs
Mon14:15-16:00HG E 5 »
Tue09:15-10:00HG E 5 »
J. M. Buhmann
252-0526-00 UStatistical Learning Theory2 hrs
Mon16:15-18:00HG E 5 »
J. M. Buhmann
252-0526-00 AStatistical Learning Theory1 hrsJ. M. Buhmann
636-0702-00LStatistical Models in Computational BiologyW6 credits2V + 1U + 2A
636-0702-00 VStatistical Models in Computational Biology
The lecture will be held either in Zurich or Basel and will be transmitted via videoconference to the second location.
2 hrs
Thu12:15-14:00BSB E 4 »
12:15-14:00HG D 16.2 »
N. Beerenwinkel
636-0702-00 UStatistical Models in Computational Biology
The tutorial will be held either in Zurich or Basel and will be transmitted via videoconference to the second location.
1 hrs
Thu14:15-15:00BSB E 4 »
14:15-15:00HG D 16.2 »
N. Beerenwinkel
636-0702-00 AStatistical Models in Computational Biology
Project work, no fixed presence required.
2 hrsN. Beerenwinkel
701-0104-00LStatistical Modelling of Spatial DataW3 credits2G
701-0104-00 GStatistical Modelling of Spatial Data2 hrs
Wed08:15-10:00CHN F 46 »
A. J. Papritz
401-6222-00LRobust and Nonlinear Regression Information Restricted registration - show details W2 credits1V + 1U
401-6222-00 VRobust and Nonlinear Regression Special students and auditors need a special permission from the lecturers.
Does not take place this semester.
12s hrs
401-6222-00 URobust and Nonlinear Regression Special students and auditors need a special permission from the lecturers.
Does not take place this semester.
9s hrs
  •  Page  1  of  2 Next page Last page     All