Lecturer(s)
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Kopárová Jitka, Ph.D.
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Zajíček Daniel, Ing. Mgr. Ph.D.
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Gašpařík Adam, doc. RNDr. Ph.D.
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Course content
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Descriptive statistics. Probability. Random variable. Special distribution of random variable. Multidimensional random variable. Central limit theorem. Random sampling. Point estimation. Interval estimation. Hypotheses testing Introduction to regression
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Learning activities and teaching methods
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Lecture with practical applications, Lecture, Practicum
- Preparation for comprehensive test (10-40)
- 40 hours per semester
- Preparation for an examination (30-60)
- 60 hours per semester
- Contact hours
- 52 hours per semester
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prerequisite |
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Knowledge |
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require the knowledge of two-semester university course of mathematics. |
explain the concepts of function of one variable |
explain the principle of derivation and integral |
explain the principle of calculation of variation, permutation and combination |
Skills |
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process basics in MS Excel |
assemble and create function in MS Excel |
derivate and integrate function |
modify algebraic expression |
solve combinatorics tasks, use variations, permutations and combinations |
Competences |
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N/A |
learning outcomes |
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Knowledge |
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Use competently basic probability and statistical methods. |
Understand the substance of these methods enough to be able to choose suitable method for concrete real situation, to verify the preconditions of its applicability. |
Apply such method correctly and to interpret its results back in practice. |
In the real situation student will be able to understand substantial circumstances of the examined random variables (from the point of view of the given purpose). Then by using probability and statistics he or she will be able to pursue analysis, synthesis, assessment and conclusion, including high quality presentation and warning about the limits of the probability deductions. |
Skills |
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select suitable method for sample file creation |
calculate characteristics of statistics file |
determine probability of simple events and probability of combination of events |
describe random variable using distribution and calculate moments of random variable |
select suitable distribution of random variable and use it for solution of practical problems |
use normal and stnadard normal distribution, quantils and table values of distribution function |
apply consequences of Central limit theorem for solution of selected probloems |
estimate parameters of population using point estimation, construct interval estimation of these parematers |
Competences |
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N/A |
teaching methods |
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Knowledge |
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Lecture |
Practicum |
Interactive lecture |
E-learning |
Self-study of literature |
Skills |
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Lecture with visual aids |
Practicum |
E-learning |
Competences |
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Interactive lecture |
E-learning |
Individual study |
assessment methods |
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Knowledge |
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Combined exam |
Skills |
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Skills demonstration during practicum |
Test |
Practical exam |
Competences |
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Practical exam |
Test |
Skills demonstration during practicum |
Recommended literature
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Bluman, A. Elementary Statistics: A Step By Step Approach. Mc Graw Hill, 2017. ISBN 1260152820.
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Lind, Douglas A.; Marchal, William G.; Wathen, Samuel A. Basic statistics for business & economics. Tenth edition, international student edition. 2022. ISBN 978-1-260-59757-8.
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Loftus, Stephen C. Basic statistics with R : reaching decisions with data. 2022. ISBN 978-0-12-820788-8.
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Newbold, P., Carlson, W., Thorne, B. Statistics for Business and Economics. Pearson Education Limited.
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