Probablity Theroy

Students will learn the complete syllabus of probability theory relevant to competitive exams. Topics covered include: basic definitions and axioms, classical and axiomatic probability, conditional probability, Bayes' Theorem, random variables, probability distributions (Binomial, Poisson, Geometric, Normal, Exponential), expectation and variance, joint distributions, covariance and correlation, and key limit theorems such as the Law of Large Numbers and the Central Limit Theorem. Each concept is explained with solved examples and exam-style MCQs with detailed solutions, so students learn both theory and application. This class is designed for students and working professionals preparing for competitive examinations such as CAT, GATE, GRE, GMAT, UPSC, JEE, and NDA. It is also ideal for undergraduate students who want to build a strong conceptual foundation in probability theory. Students should have a basic understanding of high school mathematics. A notebook and pen for working through problems are recommended. All study material, formula sheets, and practice questions will be provided during the class.