Search result: Catalogue data in Autumn Semester 2019
CAS in Applied Statistics  | ||||||
 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 | M. Tanadini | |
| Abstract | Simple and multiple regression models, with emphasis on practical aspects and interpretation of results, analysis of residuals and model selection. | |||||
| Learning 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. | |||||
| Learning 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. | |||||
Page
1
of
1
