New York University 3 credits Mathematics
Topics to be covered in this course include various statistical models (sampling model, randomization methods), estimation and margins of error (MLE, confidence intervals, asymptotic theory, efficiency and sufficiency, robustness), likelihood theory (score functions and ratio tests), Bayes theory, decision theory (hypothesis testing, goodness of fit, shrinkage), and finally, an introduction to some common computational methods (bootstrap, Markov Chain-Monte Carlo). | Prerequisites: Undergraduate level proficiency in Linear Algera and Multivariable Calculus. Graduate level proficiency in Probability, at the level of MATH-GA 2901, MA-GY 6813 or ECE-GY 6303.
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