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| Detailed information |
| Original study plan |
Bachelor's programme Artificial Intelligence 2019W |
| Objectives |
Students will become familiar with the methods presented in the corresponding lecture and can use R for solving statistical problems
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| Subject |
- 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 distribution
- Estimating parameters: point estimation and confidence interval estimation
- Statistical hypothesis testing
- Introduction into R
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| Criteria for evaluation |
Homework assignments and presentations
|
| Methods |
Student presentations
|
| Language |
English |
| Study material |
- Slides provided by instructor
- Bortz, J.: Statistik für Human- und Sozialwissenschaftler. Springer, Heidelberg, in der aktuellen Auflage.
- Fahrmeir, L.; Künstler, R.; Pigeot, I.: Statistik – Der Weg zur Datenanalyse. Springer, Berlin, in der aktuellen Auflage.
- Hartung, J.; Elpelt, B.; Klösener, K.-H.: Statistik: Lehr- und Handbuch der angewandten Statistik. Oldenbourg, München, in der aktuellen Auflage.
- or any other introductory book to statistics
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| Changing subject? |
No |
| Further information |
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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