Introduction to Probability and Statistics
The complete RGPV syllabus for Introduction to Probability and Statistics (AL302 / CD302), the third-semester course for B.Tech CSE — Artificial Intelligence & Machine Learning and Data Science under the AICTE Flexible Curricula — probability, continuous and bivariate distributions, and applied statistics through large- and small-sample tests.
Introduction to Probability & Statistics
by Dr. D.C. Agarwal & Dr. Pradeep K. Joshi · ₹440 — covers this full RGPV syllabus.
Course contents — unit by unit
Unit 1 · Basic Probability
Probability spaces, conditional probability, independence; discrete random variables, independent random variables, the multinomial distribution, Poisson approximation to the binomial, infinite sequences of Bernoulli trials, sums of independent random variables; expectation, moments, variance of a sum, correlation coefficient, Chebyshev's inequality.
Unit 2 · Continuous Probability Distributions
Continuous random variables and their properties, distribution functions and densities; normal, exponential and gamma densities.
Unit 3 · Bivariate Distributions
Bivariate distributions and their properties, distribution of sums and quotients, conditional densities, Bayes' rule.
Unit 4 · Basic Statistics
Measures of central tendency, moments, skewness and kurtosis; probability distributions (binomial, Poisson, normal) and evaluation of their parameters; correlation and regression, rank correlation.
Unit 5 · Applied Statistics
Curve fitting by the method of least squares — straight lines, second-degree parabolas and more general curves. Tests of significance — large-sample tests for single proportion, difference of proportions, single mean, difference of means and difference of standard deviations.
Unit 6 · Small Samples
Tests for single mean, difference of means and correlation coefficients; test for ratio of variances; Chi-square test for goodness of fit and independence of attributes.