Search result: Catalogue data in Autumn Semester 2017
CAS in Applied Statistics Course duration: about 12 months Next course: FS 2019 | ||||||
Compulsory Courses | ||||||
Number | Title | Type | ECTS | Hours | Lecturers | |
---|---|---|---|---|---|---|
447-0649-01L | Applied Statistical Regression I Only for DAS and CAS in Applied Statistics. | O | 4 credits | 1V + 1U | W. A. Stahel, J. Ernest | |
Abstract | Simple and multiple regression models, with emphasis on practical aspects and interpretation of results, analysis of residuals and model selection. | |||||
Objective | Understanding the multiple linear regression model and its importance for modelling and prediction. Practice of regression analyses using the statistical software R and correct interpretation of results. Model critique by analysis of residuals. Strategies for model selection. | |||||
447-0625-01L | Applied Analysis of Variance and Experimental Design I Only for DAS and CAS in Applied Statistics. | O | 3 credits | 1V + 1U | L. Meier | |
Abstract | Principles of experimental design, one-way analysis of variance, contrasts and multiple comparisons, multi-factor designs and analysis of variance, complete block designs, Latin square designs. | |||||
Objective | Participants will be able to plan and analyze efficient experiments in the fields of natural sciences. They will gain practical experience by using the software R. | |||||
Literature | G. Oehlert: A First Course in Design and Analysis of Experiments, W.H. Freeman and Company, New York, 2000. | |||||
Further Courses | ||||||
Number | Title | Type | ECTS | Hours | Lecturers | |
447-0649-02L | Applied Statistical Regression II Only for DAS and CAS in Applied Statistics. | Z | 2 credits | 1V + 1U | W. A. Stahel, J. Ernest | |
Abstract | Generalized linear models (GLMs) and basic ideas of robust regression. | |||||
Objective | Understanding the concept and flexibility of generalized linear models and correct interpretation of the corresponding model outputs. | |||||
447-0625-02L | Applied Analysis of Variance and Experimental Design II Only for DAS and CAS in Applied Statistics. | Z | 3 credits | 1V + 1U | L. Meier | |
Abstract | Random effects and mixed effects models, split-plot designs, incomplete block designs, two-series factorials and fractional designs, power. | |||||
Objective | Participants will be able to plan and analyze sophisticated experiments in the fields of natural sciences. They will gain practical experience by using the software R. | |||||
Literature | G. Oehlert: A First Course in Design and Analysis of Experiments, W.H. Freeman and Company, New York, 2000. | |||||
401-6201-00L | Nonparametric and Resampling Methods Special Students "University of Zurich (UZH)" in the Master Program in Biostatistics at UZH cannot register for this course unit electronically. Forward the lecturer's written permission to attend to the Registrar's Office. Alternatively, the lecturer may also send an email directly to Link. The Registrar's Office will then register you for the course. | Z | 2 credits | 2G | L. Meier, D. Kuonen | |
Abstract | Nonparametric tests, randomization tests, jackknife and bootstrap, as well as asymptotic properties of estimators. | |||||
Objective | For classical parametric models there exist optimal statistical estimators and test statistics whose distributions can often be determined exactly. The methods covered in this course allow for finding statistical procedures for more general models and to derive exact or approximate distributions of complicated estimators and test statistics. | |||||
Content | Nonparametric tests, randomization tests, jackknife and bootstrap, as well as asymptotic properties of estimators. | |||||
Prerequisites / Notice | This course is part of the programme for the certificate and diploma in Advanced Studies in Applied Statistics. It is given every second year in the winter semester break. |
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