Probability, Statistics and Linear programming Tuition Class
Total, Compound, Marginal and conditional probability, Bayes' theorem - Binomial, Poisson and Normal distributions, Moment generating function, Characteristic function
Central Limit Theorem, Law of large numbers, Tests of significance, large and small samples, t- test, Ftest and chi-square test for goodness of fit.
Estimation theory, ANOVA table and analysis, Multiple and partial correlation - Regression Convex spaces, LPP statement, basic feasible solution, Graphical solution - Slack and surplus variables - Artificial variable technique - Charne's penalty method - Two phase method - Dual simplex method - Primal dual problems, Transportation and Assignment problems. Integer programming - Gomory's cutting plane method - Branch and bound method
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