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Lecturer:
Prof. Dr. Angelika Steger
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Area:
3+1 lectures per week in
undergraduate studies
compulsory course
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Time and Place:
Wed 9h c.t. - 10:00, lecture hall S1128
Fri 8:30 - 10:00, lecture hall S1128
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Exercises:
1 hours per week central exercises accompanying the lectures
Tue 12h c.t. - 13:00, lecture hall 2750
Teaching Assistant: Tom Friedetzky
Course Certificate: To get a course certificate students must
pass the final exam.
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Results of the final exam.
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Audience:
undergraduate students of computer science
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Prerequisites:
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Recommended for:
Vordiplom
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Contents:
- Finite probability spaces
- Def. probability space, events, random variable
- Some distributions
- Markov and Chebychev inequalities
- Infinite probability spaces
- Normal distribution, exponential distribution
- Central limit theorem
- Stochastic processes
- Statistics
- Estimation variables
- Confidence intervals
- Checking of hypotheses
- Further Highlights
- Primality tests
- Computing the median
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Related and Advanced Lectures:
Graduate courses
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Lecture Notes:
here (in german)
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References:
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M. Greiner, G. Tinhofer:
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Stochastik für Informatiker
Carl Hanser Verlag, 1996
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H. Gordon:
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Discrete Probability
Springer-Verlag, 1997
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R. Motwani, P. Raghavan:
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Randomized Algorithms
Cambridge University Press, 1995
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L. Fahrmeir, R. Künstler, I. Pigeot, G. Tutz:
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Statistik -- Der Weg zur Datenanalyse
Springer-Verlag, 1997
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Office Hours:
look here
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