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Course info
KVV / STA2
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Course description
Department/Unit / Abbreviation
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KVV
/
STA2
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Academic Year
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2023/2024
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Academic Year
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2023/2024
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Title
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Statistics II
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Form of course completion
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Examination
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Form of course completion
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Examination
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Accredited / Credits
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Yes,
6
Cred.
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Type of completion
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Combined
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Type of completion
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Combined
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Time requirements
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Lecture
1
[HRS/WEEK]
Seminar
1
[HRS/WEEK]
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Course credit prior to examination
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Yes
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Course credit prior to examination
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Yes
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Automatic acceptance of credit before examination
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No
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Included in study average
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YES
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Language of instruction
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Czech
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Occ/max
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Automatic acceptance of credit before examination
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No
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Summer semester
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0 / 39
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0 / 0
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0 / 0
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Included in study average
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YES
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Winter semester
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0 / -
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0 / -
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0 / -
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Repeated registration
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NO
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Repeated registration
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NO
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Timetable
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Yes
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Semester taught
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Summer semester
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Semester taught
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Summer semester
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Minimum (B + C) students
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not determined
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Optional course |
Yes
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Optional course
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Yes
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Language of instruction
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Czech
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Internship duration
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0
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No. of hours of on-premise lessons |
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Evaluation scale |
A|B|C|D|E|F |
Periodicity |
každý rok
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Evaluation scale for credit before examination |
S|N |
Periodicita upřesnění |
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Fundamental theoretical course |
No
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Fundamental course |
No
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Fundamental theoretical course |
No
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Evaluation scale |
A|B|C|D|E|F |
Evaluation scale for credit before examination |
S|N |
Substituted course
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None
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Preclusive courses
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N/A
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Prerequisite courses
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KVV/STA1
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Meet all prerequisites before registering
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YES
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Informally recommended courses
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N/A
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Courses depending on this Course
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N/A
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Histogram of students' grades over the years:
Graphic PNG
,
XLS
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Course objectives:
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The objective of this course is to build on the knowledge gained in the course Statistics I. and to introduce to students the terms of statistics and the basic procedures of data analysis.
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Requirements on student
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Written examination + oral examination.
Attendance 80%.
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Content
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Statistic presumption. Testing a statistical hypothesis. Correlative and regression analysis. A pivot table.
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Activities
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Fields of study
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Guarantors and lecturers
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Literature
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Basic:
SWOBODA,H. Moderní statistika.. Praha: Svoboda, 1977.
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Basic:
EGERMAYER. F.; BOHÁČ, M. Statistika pro techniky.. Praha: SNTL, 1984.
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Basic:
CYHELSKÝ, L. Úvod do teorie statistiky.. Praha: SNTL, 1981.
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Recommended:
LIKEŠ, J.; MACHEK, J. Matematická statistika.. Praha: SNTL, 1983.
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Recommended:
SEGER, J.; HINDLS, R. Statistické metody v tržním hospodářství.. Praha: Victoria Publishing, 1995.
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Recommended:
MELOUN, M.; MILITKÝ, J. Statistické zpracování experimentálních dat.. Praha: Plus, 1994.
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Recommended:
HÁTLE, J.; LIKEŠ, J. Základy počtu pravděpodobnosti a matematické statistiky.. Praha: SNTL, 1972.
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Prerequisites - other information about course preconditions |
- |
Competences acquired |
Students will be able to understand the problems and to use the gained knowledge in the analysis of statistical data and when working with statistical software. |
Teaching methods |
- Monologic (reading, lecture, briefing)
- Methods of individual activities
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Assessment methods |
- Oral examination
- Written examination
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