Probability and Statistics

Sample space and probability theory. Density and distribution functions of single and multiple discrete and continuous random variables. Functions of random variables. Expectation, variance and transforms. Independence, covariance and correlation. Central limit theorem, weak/strong law of large numbers. Introduction to random processes. Confidence intervals, hypothesis testing, simple linear regression techniques, chi-square minimization methods.

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