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CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2016/2017

Probability And Statistics

Login to KOS for course enrollment Display time-table
Code Completion Credits Range Language
BE5B01PRS Z,ZK 7 4+2
Lecturer:
Kateřina Helisová (guarantor), Anna Pidnebesna
Tutor:
Kateřina Helisová (guarantor), Anna Pidnebesna
Supervisor:
Department of Mathematics
Synopsis:

The course covers probability and basic statistics. First classical probability is introduced, then theory of random variables is developed including examples of the most important types of discrete and continuous distributions. Next chapters contain moment generating functions and moments of random variables, expectation and variance, conditional distributions and correlation and independence of random variables. Statistical methods for point estimates and confidence intervals are investigated.

Requirements:
Syllabus of lectures:

1. Events and probability.

2. Sample spaces.

3. Independent events, conditional probability, Bayes' formula.

4. Random variable, distribution functin, quantile function, moments.

5. Independence of random variables, sum of independent random variables.

6. Transformation of random variables.

7. Random vector, covariance and correlation.

8. Chebyshev's inequality and Law of large numbers.

9. Central limit theorem.

10. Random sampling and basic statistics.

11. Point estimation, method of maximum likehood and method of moments, confidence intervals.

12. Test of hypotheses.

13. Testing of goodness of fit.

Syllabus of tutorials:

1. Events and probability.

2. Sample spaces.

3. Independent events, conditional probability, Bayes' formula.

4. Random variable, distribution functin, quantile function, moments.

5. Independence of random variables, sum of independent random variables.

6. Transformation of random variables.

7. Random vector, covariance and correlation.

8. Chebyshev's inequality and Law of large numbers.

9. Central limit theorem.

10. Random sampling and basic statistics.

11. Point estimation, method of maximum likehood and method of moments, confidence intervals.

12. Test of hypotheses.

13. Testing of goodness of fit.

Study Objective:
Study materials:

[1] Papoulis, A.: Probability and Statistics, Prentice-Hall, 1990.

[2] Stewart W.J.: Probability, Markov Chains, Queues, and Simulation: The Mathematical Basis of Performance Modeling. Princeton University Press 2009.

Note:
Time-table for winter semester 2016/2017:
06:00–08:0008:00–10:0010:00–12:0012:00–14:0014:00–16:0016:00–18:0018:00–20:0020:00–22:0022:00–24:00
Mon
roomT2:C2-86
Helisová K.
Pidnebesna A.

12:45–14:15
(lecture parallel1)
Dejvice
Cvičebna
roomT2:C2-86
Helisová K.
Pidnebesna A.

14:30–16:00
(lecture parallel1)
Dejvice
Cvičebna
roomT2:C2-86
Helisová K.
Pidnebesna A.

16:15–17:45
(lecture parallel1
parallel nr.1)

Dejvice
Cvičebna
Tue
Fri
Thu
Fri
Time-table for summer semester 2016/2017:
Time-table is not available yet
The course is a part of the following study plans:
Data valid to 2017-09-24
For updated information see http://bilakniha.cvut.cz/en/predmet4356306.html