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.
