L18 | Total Probability Theorem | Probability Class 12 Maths | JEE Mains & Advanced | скачать в хорошем качестве

L18 | Total Probability Theorem | Probability Class 12 Maths | JEE Mains & Advanced |

Total Probability Theorem Class 12 Probability for JEE Mains and Advanced explained in detail with concept building and real exam-level problems. This lecture is part of Probability Class 12 Maths course for JEE, CBSE and serious aspirants. 📘 About this Lecture (Lecture 18 – Probability) In this lecture, we study the Total Probability Theorem, one of the most important and frequently used ideas in Class 12 Probability. This concept forms the foundation for advanced applications like Bayes’ Theorem and is regularly tested in JEE Mains, JEE Advanced and CBSE board exams. The lecture begins with a strong conceptual discussion on how a sample space can be divided into different cases and how probability is calculated when an event depends on multiple possible situations. Instead of memorising results, the focus is on logical thinking, interpretation of situations and correct decision-making. You will clearly understand: How probability changes when outcomes depend on different sources Why partitioning of sample space is necessary How to approach multi-case probability questions confidently How JEE frames questions using this idea 🎯 Problems Covered in This Lecture This lecture includes exam-oriented problems based on: Selection from multiple groups or machines Defective item type questions Situation-based problems (real-life probability models) Objective questions similar to JEE Mains PYQs Each problem is discussed step-by-step with clear reasoning, so students can apply the same approach in any exam. 👨‍🎓 Who Should Watch This Lecture? Class 12 Maths students JEE Mains & JEE Advanced aspirants CBSE board students Droppers and repeaters Students preparing Probability seriously for competitive exams 📚 Playlist Link 👉 Watch the complete Probability playlist for JEE & CBSE to build concepts from basics to advanced level. Time Stmap : 00:00 – Introduction to Total Probability Theorem (Lecture overview) 02:10 – Motivating example: Two bags and selection of a ball 07:40 – Case-based thinking and why simple probability fails here 12:30 – Partition of a Sample Space (concept and definition) 18:20 – Properties of partition (mutually exclusive & exhaustive) 24:10 – Visual explanation using diagrams and regions 29:30 – Statement of Total Probability Theorem (conceptual meaning) 34:10 – Understanding how different cases contribute to one event 39:20 – Proof idea of Total Probability Theorem (logical breakdown) 44:30 – Factory & defective items problem (JEE Mains type) 50:10 – Strike and completion-time problem (application-based) 55:40 – Group selection problem (objective / MCQ pattern) 01:01:20 – Summary, key observations & exam strategy 🔖 #TotalProbabilityTheorem #ProbabilityClass12 #JEEProbability #JEEMainsMaths #JEEAdvancedMaths #Class12Maths #CBSEProbability #IITJEE #ProbabilityLecture