Statistical and Computational Methods for Electrical Engineering

Must be an expert and have knowledge in these subjects Experiments, sample spaces, events, probability, enumeration and counting techniques, conditional probability, independence Random variables, discrete probability mass functions, cumulative distributions, expectation Binomial, hypergeometric, and negative binomial probability distributions Continuous random variables, probability density functions Normal and exponential probability models Joint distributions, expectation, covariance, correlation, linear combinations Sample statistics and sampling distributions Point estimation, properties of point estimators, maximum likelihood Emphasis intervals for means, differences in means, proportions, variances; t, chi-square and F distributions Regression analysis