LPP and Markov Chains for CSIR NET Mathematics Prep

Preparing for the CSIR NET mathematical sciences exam requires a deep, conceptual understanding of applied mathematics. This text-based course is designed to help you master Linear Programming Problems (LPP) and Markov Chains, two high-scoring areas of the syllabus. Through clear, step-by-step written explanations, you will transition from memorizing formulas to confidently solving complex exam-style questions. What you'll learn: 1. Understand the foundational theory of convex sets, hyperplanes, and extreme points in LPP. 2. Solve linear programming problems using graphical methods, simplex algorithms, and duality theory. 3. Analyze Markov chains by identifying transition probability matrices, state classifications, and stationary distributions. 4. Calculate absorption probabilities and mean recurrence times for various stochastic processes. 5. Apply proven problem-solving strategies to previous exam questions and common practice patterns. The course begins with core definitions of convexity and probability spaces before moving systematically through simplex iterations, duality, Markov properties, and limiting behaviors. You will work through numerous written examples and practice exercises tailored to the exam format. This course is designed for mathematics graduates and CSIR NET aspirants who want a solid, self-paced written guide to master these specific topics, with no advanced prior knowledge of operations research required. Start reading today to sharpen your mathematical reasoning and secure vital marks in your upcoming exam.