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Statistics for Civil Engineering
| Type of study | Bachelor |
|---|---|
| Language of instruction | Czech |
| Code | 230-0206/03 |
| Abbreviation | SVS |
| Course title | Statistics for Civil Engineering |
| Credits | 4 |
| Coordinating department | Department of Mathematics |
| Course coordinator | Ing. Lukáš Pospíšil, Ph.D. |
Subject syllabus
1. Introduction to statistics, data processing, and stochastic modeling
2. Linear regression, least squares method
3. Nonlinear regression, selection of the optimal model
4. Combinatorics
5. Probability theory, Kolmogorov’s axioms
6. Conditional probability, Bayes’ theorem
7. Discrete random variable
8. Continuous random variable
9. Normal distribution
10. Parameter estimation: method of moments, maximum likelihood estimation
11. Interval estimation, central limit theorem
12. Hypothesis testing: parametric tests
13. Hypothesis testing: nonparametric tests
2. Linear regression, least squares method
3. Nonlinear regression, selection of the optimal model
4. Combinatorics
5. Probability theory, Kolmogorov’s axioms
6. Conditional probability, Bayes’ theorem
7. Discrete random variable
8. Continuous random variable
9. Normal distribution
10. Parameter estimation: method of moments, maximum likelihood estimation
11. Interval estimation, central limit theorem
12. Hypothesis testing: parametric tests
13. Hypothesis testing: nonparametric tests
E-learning
Literature
Briš, R., Škňouřilová, P.: Statistics I. Lecture notes VSB-TU, Ostrava 2007. https://mdg.vsb.cz/portal/en/Statistics1.pdf
Schreiberová, P., Rabasová, M.: Workbook for Statistics. Ostrava 2021. https://mdg.vsb.cz/portal/en/Statistics_workbook.pdf
Casella, G., Berger, R. L.: Statistical Inference. 2nd edition. Duxbury Press, Pacific Grove, 2002. ISBN 978-0-534-24312-8 .
Schreiberová, P., Rabasová, M.: Workbook for Statistics. Ostrava 2021. https://mdg.vsb.cz/portal/en/Statistics_workbook.pdf
Casella, G., Berger, R. L.: Statistical Inference. 2nd edition. Duxbury Press, Pacific Grove, 2002. ISBN 978-0-534-24312-8 .
Advised literature
Middleton, M. R.: Data Analysis Using Microsoft Excel. 5th ed. Boston: Cengage Learning, 2018. ISBN 978-1-337-40664-2 .
Hastie, T., Tibshirani, R.; Friedman, J.: The Elements of Statistical Learning: Data Mining, Inference, and Prediction. 2nd ed. New York: Springer, 2009. ISBN 978-0-387-84857-0. https://statweb.stanford.edu/~tibs/ElemStatLearn/
Hastie, T., Tibshirani, R.; Friedman, J.: The Elements of Statistical Learning: Data Mining, Inference, and Prediction. 2nd ed. New York: Springer, 2009. ISBN 978-0-387-84857-0. https://statweb.stanford.edu/~tibs/ElemStatLearn/