Contents

• Unit 1. Introduction: Objective, scope and outcome of the course.

   

  Unit 2. Probability: Basic concepts of probability, conditional probability, Baye’s theorem. Random variable: Discrete and Continuous random variables, Joint distribution, Marginal distribution, Probability distribution function, Conditional distribution.Mathematical Expectations: Moments, Moment Generating Functions, variance and correlation coefficients, Chebyshev’s Inequality, Skewness and Kurtosis. Binomial, Poisson and Normal distribution and their properties.

   

  Unit 3. Applied Statistics: Basic concept of variance, Correlation and regression – Rank correlation. Curve fitting by the method of least squares- fitting of straight lines, second degree parabolas and more general curves. Test of significance: Large sample test for single proportion, difference of proportions, single mean, difference of means, and difference of standard deviations.