Probability:
concept of a random experiment and sample space; addition and multiplication
laws of probability; conditional probability and independence, Bay’s theorem
and its application. Random variables and their probability distribution;
Binomial, Poisson, Normal, Gamma, Exponential, Uniform and Cauchy distributions
and their properties.
Basic statistical concepts: Statistical data, measures of
central simple linear regression, regression coefficient and correlation
coefficient, non-linear regression. Fitting of linear and non-linear regression
to data. Multiple linear regression and multiple correlation coefficient.
