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| Detailinformationen |
| Quellcurriculum |
Bachelorstudium Artificial Intelligence 2019W |
| Ziele |
(*)Introduction into the research methodology in statistics and the basic principles of statistical thinking
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| Lehrinhalte |
(*)- Descriptive statistics: one and two dimensional characteristics
- Correlation and linear regression
- Basic concept of probability theorie including Bayes' theorem
- Theory of random variables
- Special distributions, test distributions
- Estimating parameters: point estimation and interval estimation
- Statistical hypothesis testing
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| Beurteilungskriterien |
(*)Examination
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| Lehrmethoden |
(*)Lecture by instructor
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| Abhaltungssprache |
Englisch |
| Literatur |
(*)- Slides provided by instructor
- Bortz, J.: Statistik für Human- und Sozialwissenschaftler. Springer, Heidelberg
- Fahrmeir, L.; Künstler, R.; Pigeot, I.: Statistik – Der Weg zur Datenanalyse. Springer, Berlin
- Hartung, J.; Elpelt, B.; Klösener, K.-H.: Statistik: Lehr- und Handbuch der angewandten Statistik. Oldenbourg
- or any other introductory book to statistics
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| Lehrinhalte wechselnd? |
Nein |
| Sonstige Informationen |
(*)Continuative courses:
- Statistics 2 (focus on parametric and non-parametric tests)
- Special Topics: Computer Assisted Statistics with SPSS (introduction into SPSS)
- Special Topics: Biostatistics in Clinical Research (introduction into biostatisics)
- Special Topics: Applied Biostatistics
- Special Topics: Statistics 3 (parametric and non-parametric analysis of variance, multiple linear and non-linear regression )
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