Course No:           Act 411

Course Name:      Mathematical Statistics

Course Description:      

a) Random Variable, Distribution functions, Probability density function: Expectations. c.d.f., Moments and Moment generating function: Characteristic function & Cumulants.

b) Some Univariate Distributions. Uniform, Exponential, Beta, Gamma and Normal Distributions. Their derivation, properties and uses.

c) Law of large number (with examples); Central limit theorem and Chebyshev’s inequality, Transformations in univariate distributions.

d) Joint and Conditional Density Functions. Conditional Expectations, Statistic Independence. Transformations in bivariate Distributions.

e) Bivariate Distributions. Conditional and marginal distributions. Bivariate Normal and its properties, Multinomial distributions.

f) Basic ideas of functional and stochastic independence, Covariance and linear correlation.

Course Review:

This course signifies the usage of random variables, distribution functions, probability density functions, expectations, cdf, moments and moment generating functions, some univariate distributions, joint and conditional density functions, law of large numbers, conditional expectations, statistical independence, conditional and marginal distributions, multinomial distributions, bivariate distributions and transformation in bivariate distributions.