151-0501/01 – Probability and Statistics A ()
Gurantor department | Department of Mathematical Methods in Economics | Credits | 4 |
Subject guarantor | RNDr. Matěj Turčan, Ph.D. | Subject version guarantor | RNDr. Matěj Turčan, Ph.D. |
Study level | undergraduate or graduate | Requirement | Compulsory |
Year | 2 | Semester | winter |
| | Study language | Czech |
Year of introduction | 1992/1993 | Year of cancellation | 2007/2008 |
Intended for the faculties | EKF | Intended for study types | Master |
Subject aims expressed by acquired skills and competences
Teaching methods
Summary
The introductory course Probability and Statictics A deals with the basic
problems of probability and statistics. It gives the base for ability to
describe random processes in Economics by means of random variable and random
vector. It builds the base of Descriptive statistics.
Compulsory literature:
Recommended literature:
Way of continuous check of knowledge in the course of semester
E-learning
Other requirements
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
1. Algebra of Events (Random Event, Event Relations and Operations, Sample
Space)
2. Partition of the Sample Space. Field of Events. Concept of Probability
(Axioms, Theorems, Definitions).
3. Probability and Event Operations. Conditional Probability. Independent
Event.
4. Succession of Independent Events. Total Probability. Bayes' Rule.
5. Random Variable - definition, types. Probability Distribution -
Distribution
Function, Frequency Functions.
6. Discrete Probability Distributions - Uniform, Binomial, Hypergeometric,
Geometric, Pascal's, Poisson'n,...Approximation of Binomial Distribution.
7. Continuous Probability Distributions - Uniform, Exponential.
8. Normal Distribution. Special Distributions (Pearson's, Student's, Fisher-
Snedecor's).
9. Descriptive Measures of Random Variables I. Classification of Descriptive
Measures.
10. Descriptive Measures of Random Variables II. Moment Generating Function.
11. Random Vector - definition, types. Join, Marginal and Conditional
Probability Distributions.
12. Descriptive Measures of Random Vector.
13. Regression Polygons and Lines. Limit Theorems.
14. Set of Values of One Variable - Range, Frequency
Distribution, Cumulative, Relative, Cumulative Relative Frequencies and its
Graphs.
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction
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