Probability and Statistics

Course Description

Sample space and events, axioms of probability; Conditional probability, independence and the Bayes Rule; Random variables, discrete probability distribution, continuous probability distribution, joint probability distribution; Mean, variance, covariance and correlation; Some discrete probability distributions: uniform, binomial, hyper geometric, geometric, negative binomial and Poisson; Some continuous probability distributions: normal, exponential, gamma, chi-Squared, lognormal and Weibull; Sampling distributions; Confidence intervals; Hypotheses Testing; Regression and correlation analysis.



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