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Main menu for Browse IS/STAG
Course info
KMA / PSA
:
Course description
Department/Unit / Abbreviation
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KMA
/
PSA
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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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Probability and Statistics A
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Form of course completion
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Exam
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Form of course completion
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Exam
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Accredited / Credits
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Yes,
5
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
3
[Hours/Week]
Tutorial
2
[Hours/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, English
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Occ/max
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|
|
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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 / -
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0 / -
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0 / -
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Included in study average
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YES
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Winter semester
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104 / -
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0 / -
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2 / -
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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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Winter semester
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Semester taught
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Winter semester
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Minimum (B + C) students
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1
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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, English
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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 |
1|2|3|4 |
Periodicity |
každý rok
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Evaluation scale for credit before examination |
S|N |
Periodicita upřesnění |
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Fundamental theoretical course |
Yes
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Fundamental course |
Yes
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Fundamental theoretical course |
Yes
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Evaluation scale |
1|2|3|4 |
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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KMA/PSA-A
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Prerequisite courses
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N/A
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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
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XLS
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Course objectives:
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The aim of this course is to introduce basic ideas and methods of probability and statistical analysis.
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Requirements on student
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1) Before taking exam : To achieve at least 50% points in two written tests during term.
2) Exam: Be successfull both in written and in oral part of the exam. Student should have a good knowlege and comprehension of course content (incl. probability and geometric interpretation), and a good ability to apply it in examples. Short oral part follows the written one.
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Content
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Events and their probabilities.
General theory on discrete and continuous random variables.
Hypergeometric, binomial and Poisson distributions.
Exponential and normal distributions.
The central limit theorem. Quantiles of a continuous distribution.
Transformation of a random variable. Log-normal, Student and chi-square distributions.
Descriptive statistics. Estimates of parameters.
General procedure for testing hypotheses. Testing a claim about a mean. Tests of variances.
Correlation. Tests comparing two parameters. F-distribution.
Chi-square test of goodness of fit. Contingency tables.
Regression analysis. Coefficient of determination. Multiple regression.
Reliability function, failure rate. Weibull distribution. Sum of random variables. Gamma distribution.
Uses and abuses of statistics.
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Activities
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Fields of study
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Guarantors and lecturers
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-
Guarantors:
RNDr. Blanka Šedivá, Ph.D. (100%),
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Lecturer:
RNDr. Zdeněk Kobeda (100%),
RNDr. Blanka Šedivá, Ph.D. (100%),
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Tutorial lecturer:
Mgr. Michal Friesl, Ph.D. (100%),
RNDr. Zdeněk Kobeda (100%),
RNDr. Blanka Šedivá, Ph.D. (100%),
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Literature
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Basic:
Reif, J. Metody matematické statistiky. Plzeň : Západočeská univerzita, 2004. ISBN 80-7043-302-7.
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Basic:
Reif, Jiří; Kobeda, Zdeněk. Úvod do pravděpodobnosti a spolehlivosti. 1. vyd. Plzeň : Západočeská univerzita, 2000. ISBN 80-7082-702-5.
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Recommended:
Rosner, Bernard. Fundamentals of biostatistics. Belmont: Brooks/Cole, 2010. ISBN 978-0-538-73349-6.
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Recommended:
Devore, Jay L. Probability and statistics for engineering and the sciences. Boston, MA: Brooks/Cole, Cengage Learning, 2012. ISBN 978-0-538-73349-6.
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Recommended:
Ayyub, Bilal M.; McCuen, Richard H. Probability, statistics, and reliability for engineers and scientists. Third edition. 2011. ISBN 978-1-4398-0951-8.
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Recommended:
Brousek, Jan; Ryjáček, Zdeněk. Sbírka řešených příkladů z počtu pravděpodobnosti. 1. vyd. Plzeň : Západočeská univerzita, 1999. ISBN 80-7082-063-2.
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On-line library catalogues
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Time requirements
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All forms of study
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Activities
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Time requirements for activity [h]
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Contact hours
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65
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Preparation for an examination (30-60)
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45
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Preparation for comprehensive test (10-40)
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20
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Preparation for formative assessments (2-20)
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10
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Total
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140
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Prerequisites
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Knowledge - students are expected to possess the following knowledge before the course commences to finish it successfully: |
aplikovat základy diferenciálního počtu při analýze prúběhu funkce |
formulovat základní kombinatorické úvahy |
interpretovat geometrický význam určitého integrálu |
zvolit vhodný postup při řešení jednoduchých kombinatrorických úloh |
Skills - students are expected to possess the following skills before the course commences to finish it successfully: |
analyzovat průběh a extrémy funkce |
načrtnout grafy elementárních funkci |
spočítat derivaci a integrál funkce reálné proměnné ( v rozsahu M1, resp.MA1, resp. M1S ) |
upravit výrazy s kombinačními čísly a faktoriály |
Competences - students are expected to possess the following competences before the course commences to finish it successfully: |
N/A |
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Learning outcomes
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Knowledge - knowledge resulting from the course: |
formulovat statistickou hypotézu |
realizovat základní metody regresní a korelační analýzy |
rozpoznat základní typy diskrétních a spojitých rozdělení pravděpodobnosti |
vybrat vhodný statistický test pro test hypotézy |
využít diferenciálního a integrálního počtu k výpočtúm pravděpodobností |
zvolit vhodný plán pro statistické experimenty |
Skills - skills resulting from the course: |
interpretovat správně statistické výsledky |
použít metod popisné statistiky k shrnutí informací z dat |
spočítat pravděpodobnost a podmíněnou pravděpodobnost jevu |
vypočítat bodové a intervalové odhady parametru rozdělení |
vypočítat základní charakteristiky diskrétních a spojitých typů rozdělení pravděpodobnosti |
zhodnotit vhodnost použitého resgesního modelu |
Competences - competences resulting from the course: |
N/A |
N/A |
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Assessment methods
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Knowledge - knowledge achieved by taking this course are verified by the following means: |
Combined exam |
Test |
Skills - skills achieved by taking this course are verified by the following means: |
Combined exam |
Test |
Competences - competence achieved by taking this course are verified by the following means: |
Combined exam |
Test |
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Teaching methods
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Knowledge - the following training methods are used to achieve the required knowledge: |
Lecture |
Practicum |
Self-study of literature |
Task-based study method |
Skills - the following training methods are used to achieve the required skills: |
Lecture |
Practicum |
Self-study of literature |
Task-based study method |
Competences - the following training methods are used to achieve the required competences: |
Lecture |
Practicum |
Self-study of literature |
Task-based study method |
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