COURSE DETAIL
COURSE DETAIL
COURSE DETAIL
This course discusses different concepts of numerical analysis including algorithms, stability, accuracy, and efficiency. Topics include: errors, algorithms, and estimates; nonlinear equations and nonlinear systems; methods for linear systems of equations; polynomial interpolation-- Lagrange, Hermite, piecewise, and splines; numerical quadrature and differentiation.
Prerequisites: Linear Algebra, Differential Calculus, Integral Calculus, and Programming.
COURSE DETAIL
COURSE DETAIL
COURSE DETAIL
COURSE DETAIL
COURSE DETAIL
Topics cover include: Bivariate probability, continuous densities, generating functions. The exponential densities, including normal, t-, χ2 and F. Simple parametric and nonparametric tests. Further topics include the consistency, efficiency and sufficiency of estimates, maximum likelihood estimation; the central limit theorem, Chebyshev's inequality, the Neyman-Pearson lemma and the likelihood ratio test; regression, and analysis of variance.
COURSE DETAIL
COURSE DETAIL
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