STA_z Statistics

Institute of Technology and Business in České Budějovice
winter 2022
Extent and Intensity
2/4/0. 7 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
STA_z/P01: Mon 9:40–11:10 B1, M. Telecký
STA_z/S01: Mon 8:00–9:30 D316, Tue 8:00–9:30 D316, J. Šedivý
STA_z/S02: Mon 14:50–16:20 D316, Mon 16:30–18:00 D316, J. Šedivý
STA_z/T3: Sat 1. 10. 8:00–9:30 B4, 9:40–11:10 B4, 11:25–12:55 B4, 13:05–14:35 B4, 14:50–16:20 B4, 16:30–18:00 B4, Sat 12. 11. 8:00–9:30 B4, 9:40–11:10 B4, 11:25–12:55 B4, 13:05–14:35 B4, 14:50–16:20 B4, 16:30–18:00 B4, M. Telecký
Prerequisites (in Czech)
MAT_2z Mathematics II && INF_1z Informatics I.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 23 fields of study the course is directly associated with, display
Course objectives supported by learning outcomes
The aim of the course is to acquaint students with the basic procedures in the field of statistical induction, methods of analysis of qualitative and quantitative features and with the elements of time series analysis. After completing the course, the student is able to 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 is able to collect, sort, process and present statistical data.
Learning outcomes
After the successful completion of the course, the student masters the basic procedures in the field of statistical induction, methods of analysis of qualitative and quantitative features and with time series analysis elements. The student is able to collect, process and present statistical data.
Syllabus
  • 1. Methods of descriptive statistics. 2. Basic statistical characteristics and indices. 3. Probability and distribution of probabilities and their numerical characteristics. 4. Basic probability models. 5. Sample surveys, distribution of sampling characteristics and basics of statistical induction. 6. Testing statistical hypotheses. 7. Two-sample tests. 8. Further tests and analysis of variance. 9. Simple linear regression and correlation. 10. Statistical induction in regression model. 11. Multidimensional regression and prognostic application of regression. 12-13. Introduction to time series analysis.
Literature
    required literature
  • ARLTOVÁ, M., D. BÍLKOVÁ, P. ČENČÍK, E. JAROŠOVÁ, I. PECÁKOVÁ a Z. POUROVÁ, 2014. Základy statistiky v příkladech. Tribun EU, 192 s. ISBN 978-80-263-0756-3.
  • MAREK, L. a kol., 2013. Statistika v příkladech. Praha: Profesional Publishing. ISBN 978-80-7431-218-5.
  • STUCHLÝ, J., 2015. Statistické analýzy dat: vysokoškolská učebnice. 1. Vydání. České Budějovice: Vysoká škola technická a ekonomická v Českých Budějovicích, 220 s. ISBN 978-80-7468-087-8.
    recommended literature
  • HINDLS, R. a kol., 2006. Statistika pro ekonomy. Praha: Professional Publishing, ISBN 80-86946-16-9.
Forms of Teaching
Lecture
Seminar
Exercise
Excursion - language
Tutorial
Consultation
Teaching Block - tutorial
Teaching Methods
Frontal Teaching
Group Teaching - Competition
Group Teaching - Cooperation
Group Teaching - Collaboration
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
Preparation for presentation of the semester work1414
Presentation2020
Preparation for the Mid-term Test826
Preparation for Lectures5 
Preparation for Seminars, Exercises, Tutorial1528
Preparation for the Final Test2626
Project preparation1616
Attendance on Lectures26 
Attendance on Seminars/Exercises/Tutorial/Excursion5252
Total:182182
Assessment Methods and Assesment Rate
Test – mid-term 30 %
Test – final 70 %
Exam conditions
Full-time study: 1) Ongoing tests (weekly) - maximum 30 points. 2) Final test - maximum 70 points. Combined Studies: 1) Continuous tests - regularly according to the schedule for combined study - maximum 30 points. 2) Exam test - maximum 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.
The course is also listed under the following terms winter 2017, winter 2018, winter 2019, summer 2020, winter 2020, summer 2021, winter 2021, winter 2023, winter 2024.
  • Enrolment Statistics (winter 2022, recent)
  • Permalink: https://is.vstecb.cz/course/vste/winter2022/STA_z