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Statistics for Civil Engineering

Summary

The course provides students with a foundation in probability, combinatorics, and statistics, with a focus on applications in civil engineering. Emphasis is placed on the importance of data processing in technical practice, where real-world measurements often exhibit uncertainty or deviation, and their correct interpretation is crucial for decision-making in engineering tasks. Students will become familiar with discrete and continuous random variables, probabilistic models, and statistical estimation methods. The course offers a theoretical basis for understanding randomness and working with measurement error, which is commonly reflected in building codes and engineering standards. Covered topics include data analysis, hypothesis testing, and both linear and nonlinear regression methods. The course also includes point and interval estimation of distributions based on sample data. The practical part of the course takes place in Microsoft Excel, where students gain hands-on experience with statistical tools and methods used in data analysis within civil engineering practice.

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 .

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/


Language of instruction čeština, angličtina
Code 230-0206
Abbreviation SVS
Course title Statistics for Civil Engineering
Coordinating department Department of Mathematics
Course coordinator Ing. Lukáš Pospíšil, Ph.D.