Summary
Full Transcript
Welcome to Week 7 Lecture 4 of the course "Statistics for Data Science - I" by Prof. Andrew Thangaraj. Full Course: https://study.iitm.ac.in/ds/course_pages/BSMA1002.html Video Overview This lecture introduces the concept of independent events in probability and connects it to the ideas of joint, marginal, and conditional probabilities. Building on the multiplication rule, the lecture explains what it means for events to be independent and how this independence impacts conditional probability. Through simple and intuitive examples such as coin toss experiments, we explore the formal definition of independence and understand how to verify it using intersection and individual probabilities. This session strengthens your understanding of how event relationships shape probability outcomes. About IIT Madras' online Bachelor of Science programme IIT Madras offers four-year BS programmes that aim to provide quality education to all, irrespective of age, educational background, or location. The BS programme has multiple levels, which provide flexibility to students to exit at any of these levels. Depending on the courses completed and credits earned, the learner can receive a Foundation Certificate from IITM CODE (Centre for Outreach and Digital Education), Diploma(s) from IIT Madras, or BSc/BS Degrees from IIT Madras. For more details, Visit: https://www.iitm.ac.in/academics/study-at-iitm/non-campus-bs-programmes #IndependentEvents #Probability #ConditionalProbability #JointProbability #MarginalProbability #Statistics #MultiplicationRule #ProbabilityTheory #Events #SampleSpace #ProbabilityIntersection #QuantitativeMethods #StatisticalLearning #DataScienceEducation #ProbabilityConcepts
Continue this lesson in the app
Install CourseHive on Android or iOS to keep learning while you move.
