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Lecturer Dr. Perel Efrat

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Courses

  • Data Science for Engineers (19102)
    • Course summary:

    Abstract:

    Descriptive statistics, estimation, properties of estimators and estimation methods, Confidence intervals, testing of statistical hypothesis, tests about the expectation and proportion of a population, goodness of fit and independence tests, simple linear regression logistic regression. Using data analysis software.
  • Stochastic Models (40120)
    • Course summary:

    Abstract:

    Binomial and Poisson Processes, Markov Chains in discrete and continuous time - Steady-state analysis and limiting distributions. Birth and Death Processes, Queuing Theory – Poisson i?nput and Exponential service, special Queuing systems.
  • Introduction to Probability (90911)
    • Course summary:

    Abstract:

    Basic concepts in probability theory: sample space, elementary theorems, combinatorial calculations, conditional probability and independence, random discrete variables, expected value and variance, special random variables,

     multivariate variables, central limit theorem. Basic concepts in statistics: statistical estimation and testing, confidence intervals.