B_STT Statistics for engineers

Institute of Technology and Business in České Budějovice
summer 2026
Extent and Intensity
2/2. 5 credit(s). Type of Completion: zk (examination).
Teacher(s)
Ing. Jarmila Drozdová, Ph.D. (seminar tutor)
Guaranteed by
Ing. Jarmila Drozdová, Ph.D.
The Department of Mechanical Engineering – School of Expertness and Valuation – Rector – Institute of Technology and Business in České Budějovice
Supplier department: The Department of Mechanical Engineering – School of Expertness and Valuation – Rector – Institute of Technology and Business in České Budějovice
Timetable of Seminar Groups
B_STT/P01: each odd Monday 8:00–11:00 I301( spojená s I302), J. Drozdová
B_STT/S01: each odd Monday 14:50–17:50 I301( spojená s I302), J. Drozdová
Course Enrolment Limitations
The course is offered to students of any study field.
Course objectives supported by learning outcomes
The aim of the course is to introduce students to the fundamentals of statistical analysis and the principles of statistical data evaluation methods. Emphasis is placed on the use of traditional and non-parametric methods, their application, and practical utilization. Within the course, students acquire the ability to rigorously process and analyze experimental data. They learn to independently select appropriate statistical methods, apply them to real data, and subsequently evaluate and interpret the results.
Learning outcomes
Upon successful completion of the course, the student is able to define the basic procedures of statistical inference, characterize and apply methods for the analysis of qualitative and quantitative variables, and rigorously process and evaluate experimental data. The graduate is also able to independently collect, classify, process, and present statistical data.
Syllabus
Lectures 1.Methods of descriptive statistics. 2.Basic statistical characteristics and indices. 3.Probability, probability distributions and their numerical characteristics. 4.Basic probabilistic models. 5.Sample surveys, distributions of sample characteristics, and the basics of statistical inference. 6.Testing statistical hypotheses. 7.Two-sample tests. 8.Additional tests and analysis of variance. 9.Simple linear regression and correlation. 10.Statistical inference in the regression model. 11.Multiple regression and predictive applications of regression. 12.–13. Time series analysis. Seminars: 1. Data preparation for statistical analysis, including issues of value recording (decimal places), rounding, and missing values (detection limits). 2. Introduction to spreadsheet software (MS Excel) and statistical software (depending on current availability). 3. Exploratory data analysis – graphical diagnostics. 4. Exploratory data analysis – statistical tests. 5. Exploratory data analysis – outliers and data transformations. 6. Basic statistical characteristics – classical and robust estimators of central tendency and variability. 7. Interval estimation – confidence interval. 8. Issues with small samples – estimators of central tendency and variability. 9. The significance level. 10. Parametric hypothesis tests. 11. Nonparametric hypothesis tests. 12. Linear regression and correlation analysis 13. Analysis of variance (ANOVA).
Literature
    required literature
  • MOŠNA, F., 2017. Základní statistické metody. Praha: Univerzita Karlova v Praze - Pedagogická fakulta. ISBN 978-80- 7290-972-8.
  • NEUBAUER, J.; SEDLAČÍK, M. a KŘÍŽ, O. Základy statistiky: aplikace v technických a ekonomických oborech. 3., rozšířené vydání. Praha: Grada Publishing, 2021. ISBN 978–80–271–3421–2.
  • • MELOUN, M. a MILITKÝ, J. Interaktivní statistická analýza dat. Vyd. 3., Praha: Karolinum, 2012. ISBN 978-80-246-2173-9.
  • • DROZDOVÁ, J. a HOMOLA, V. Statistika pro Geovědní a montánní turismus: učební texty předmětu Statistika a informatika - část Statistika. Ostrava: Vysoká škola báňská - Technická univerzita Ostrava, 2017. ISBN 978-80-248-4067-3.
  • JANÁČEK, J.. Statistika jednoduše: průvodce světem statistiky. Praha: Grada Publishing, 2022. ISBN 978-80-271-1738- 3.
    recommended literature
  • • WILCOX, Rand R. Basic statistics: understanding conventional methods and modern insights. New York: Oxford University Press, 2009. ISBN 978-0195315103.
  • • MELOUN, M. a MILITKÝ, J. Kompendium statistického zpracování dat. 3. vyd. Praha: Karolinum, 2012. ISBN 978-80-246-2196-8.
  • • DROZDOVÁ, Jarmila. 2014. Environmentální data - metody statistického vyhodnocení. [CD]. Ostrava: ENET, VŠB-TU Ostrava.
  • • OTT, L. a LONGNECKER, M. An introduction to statistical methods & data analysis. Seventh edition. Boston, MA: Cengage Learning, [2016]. ISBN 978-1-305-26947-7.
Organizační formy výuky
Lecture
Seminar
Tutorial
Komplexní výukové metody
Frontal Teaching
Group Teaching - Competition
Group Teaching - Cooperation
Project Teaching
Brainstorming
Critical Thinking
Individual Work– Individual or Individualized Activity
Teaching Supported by Multimedia Technologies
E-learning
Student Workload
ActivitiesNumber of Hours of Study Workload
Daily StudyCombined Study
Homework - presentation16 
Preparation for the Mid-term Test10 
Preparation for Lectures13 
Preparation for Seminars, Exercises, Tutorial26 
Preparation for the Final Test13 
Attendance on Lectures26 
Attendance on Seminars/Exercises/Tutorial/Excursion26 
Total:1300
Metody hodnocení a jejich poměr
Exam – written 70%
Test – mid-term 15%
Seminary Work 15%
Podmínky testu
Grading of the course: First Test/Seminar Work/ … : maximum 30% (0-30 points), Final Test: maximum 70% (0-70 points). Successful graduates of the course have to get totally at least 70 points: A 100 – 90, B 89,99 – 84, C 83,99 – 77, D 76,99 – 73, E 72,99 – 70, FX 69,99 – 30, F 29,99 - 0.
Language of instruction
Czech
Teacher's information
Attendance in lessons is defined in a separate internal standard of ITB(Evidence of attendance of students at ITB). It is compulsory, except of the lectures, for full-time students to attend 70 % lesson of the subjet in a semester.
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