SPT Statistics for engineers

Institute of Technology and Business in České Budějovice
summer 2025
Extent and Intensity
2/2. 5 credit(s). Type of Completion: zk (examination).
Teacher(s)
Ing. Josef Šedivý (seminar tutor)
Ing. Martin Telecký, Ph.D. (seminar tutor)
Guaranteed by
Ing. Martin Telecký, Ph.D.
Department of Informatics and Natural Sciences – Faculty of Technology – Rector – Institute of Technology and Business in České Budějovice
Supplier department: Department of Informatics and Natural Sciences – Faculty of Technology – Rector – Institute of Technology and Business in České Budějovice
Timetable of Seminar Groups
SPT/P01: Mon 13:05–14:35 E1, M. Telecký
SPT/S01: Wed 13:05–14:35 D315, J. Šedivý
SPT/S02: Mon 14:50–16:20 D316, J. Šedivý
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 basic procedures in the field of statistical induction, methods of analysis of qualitative and quantitative traits and the elements of time series analysis.
Learning outcomes
After completing the course, the student can define the basic procedures in the field of statistical induction, can characterize and apply methods of analysis of qualitative and quantitative features and elements of time series analysis. The graduate can collect, sort, process and present statistical data.
Syllabus
  • 1. Methods of descriptive statistics.
  • 2. Basic statistical characteristics and indices.
  • 3. Probability and probability distributions and their numerical characteristics.
  • 4. Basic probability models.
  • 5. Sample surveys, distribution of sample characteristics and basics of statistical induction.
  • 6. Statistical hypothesis testing.
  • 7. Two-sample tests.
  • 8. Additional tests and analysis of variance.
  • 9. Simple linear regression and correlation.
  • 10. Statistical induction in a regression model.
  • 11. Multivariate regression and forecasting application of regression.
  • 12.- 13. Time series analysis.
Literature
    required literature
  • MOŠNA, F., 2017. Základní statistické metody. Praha: Univerzita Karlova v Praze - Pedagogická fakulta. ISBN 978-80- 7290-972-8.
  • JANÁČEK, J.. Statistika jednoduše: průvodce světem statistiky. Praha: Grada Publishing, 2022. ISBN 978-80-271-1738- 3.
  • 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.
    recommended literature
  • MOŠNA, F., 2017. Základní statistické metody. Praha: Univerzita Karlova v Praze - Pedagogická fakulta. ISBN 978-80- 7290-972-8.
  • ARLTOVÁ, M., 2014. Základy statistiky v příkladech. Brno: Tribun EU. ISBN 978-80-263-0756-3.
Forms of Teaching
Lecture
Seminar
Teaching Methods
Frontal Teaching
Group Teaching - Competition
Project Teaching
Brainstorming
Critical Thinking
Individual Work– Individual or Individualized Activity
Teaching Supported by Multimedia Technologies
Student Workload
ActivitiesNumber of Hours of Study Workload
Daily StudyCombined Study
Preparation for the Mid-term Test10 
Preparation for Lectures4 
Preparation for Seminars, Exercises, Tutorial4480
Preparation for the Final Test2034
Attendance on Lectures26 
Attendance on Seminars/Exercises/Tutorial/Excursion2616
Total:130130
Assessment Methods and Assesment Rate
Test – mid-term 30 %
Test – final 70 %
Exam conditions
To successfully complete the course, it is necessary to achieve the sum of the continuous and final assessment of at least 70% under the conditions set out below. V~30 points can be obtained in the continuous assessment, i.e. 30%. In the final assessment, it is possible to a total of 70 points, i.e. 70 %. Intermediate evaluation Intermediate test - 30 points (i.e. 30 %) Final assessment Final test - 70 points (i.e. 70%) 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
A full-time student is obliged to attend contact classes, i.e. everything except lectures, meet the mandatory 70% attendance.
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