Probabilty Theory For EE
2018–19–A
Prof. Ariel Yadin
Course Content
The aim of the course is to study main principles of probability theory. Such themes as probability spaces, random variables, probability distributions are given in details.Some applications are also considered.1. Probability space: sample space, probability function, finite symmetric probability space, combinatorial methods, and geometrical probabilities.2. Conditional probability, independent events, total probability formula, Bayes formula. 3. Discrete random variable, special distributions: uniform, binomial, geometric, negative binomial, hypergeometric and Poisson distribution. Poisson process.4. Continuous random variable, density function, cummulative distribution function. Special distributions: uniform, exponential, gamma and normal. Transformations of random variables. Distribution of maximum and minimum. Random variable of mixed type.5. Moments of random variable. Expectation and variance. Chebyshev inequality.6. Random vector, joint probability function, joint density function, marginal distributions. Conditional density, covariance and correlation coefficient.7. Central Limit Theorem. Normal approximation. Law of Large Numbers.
University course catalogue: 201.1.9831
Students' Issues
- Class Representative
- ספיר פאבלוקס
- Aguda Representative
- רכזת סיוע אקדמי - הנדסה א’ - יהלי ישי
- Staff Observers
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- ד”ר אמיר שלוינסקי (Electrical engineering)
- ג’וזף טבריקיאן (Electrical engineering)
- ד”ר יניב ציגל (Biomedical engineering)
- פרופ’ עופר דונחין (Biomedical engineering)
- ד”ר אסף כהן (Communication systems engineering)
- פרופ’ חן אבין (Communication systems engineering)
- עמי ישעיה (Faculty - Engineering)
- אביטל אדרי (Faculty - Engineering)
- ד”ר עדן כלמטץ’ (Computer science)
- פרופ’ דני ברנד (Computer science)
- חן קיסר (Computer science)
- אהד בן-שחר (Computer science)
- מיכאל גדלין (Faculty - Natural sciences)
- רויטל בינדר (Faculty - Natural sciences)
- פרופ’ דורון כהן (Physics)
- פרופ’ מיכאל ליובלינסקי (Physics)