Basic materials are available on the educator's website:
http://homel.vsb.cz/~bri10,
Teaching,
Prob & Stat.pdf
Basic Methods of Statistical Data Analysis in Practice
| Type of study | Doctoral |
|---|---|
| Language of instruction | English |
| Code | 470-6403/02 |
| Abbreviation | SMIP |
| Course title | Basic Methods of Statistical Data Analysis in Practice |
| Credits | 10 |
| Coordinating department | Department of Applied Mathematics |
| Course coordinator | prof. Ing. Radim Briš, CSc. |
Subject syllabus
Lectures:
- Exploratory data analysis, types of variables, summarization of distributions. Probability theory.
- Random variable and probability distribution, expected value operator and moments of probability distribution, joint and conditional distributions.
- Probability models for discrete and continuous random variables.
- Sampling distributions of the mean, distribution of sample proportion.
- Point and interval estimation, hypothesis testing, pure significance tests, p-values Two sample tests, paired difference tests.
- One factor analysis of variance, ANOVA table, multiple comparisons, post hoc analysis.
- Simple linear regression model.
- Multiple regression models.
- Exploratory data analysis, types of variables, summarization of distributions. Probability theory.
- Random variable and probability distribution, expected value operator and moments of probability distribution, joint and conditional distributions.
- Probability models for discrete and continuous random variables.
- Sampling distributions of the mean, distribution of sample proportion.
- Point and interval estimation, hypothesis testing, pure significance tests, p-values Two sample tests, paired difference tests.
- One factor analysis of variance, ANOVA table, multiple comparisons, post hoc analysis.
- Simple linear regression model.
- Multiple regression models.
E-learning
Literature
Briš R., Probability and Statistics for Engineers, 2011, electronics script, Project CZ.1.07/2.2.00/15.0132. Dostupné z http://homel.vsb.cz/~bri10/Teaching/Prob%20&%20Stat.pdf
Hastie T., Tibshirani R., Friedman J.: The Elements of Statistical Learning, Data Mining, Inference, and Prediction. Second Edition, Springer 2008.
Hastie T., Tibshirani R., Friedman J.: The Elements of Statistical Learning, Data Mining, Inference, and Prediction. Second Edition, Springer 2008.
Advised literature
James L.Johnson; Probability and Statistics for Computer Science, Wiley 2003, ISBN 0-471-32672-0