Statistics for Data Science 1 - W6_L1: Probability - basic definitions

Welcome to Week 6 Lecture 1 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 Dive into the fundamentals of probability.This lecture introduces key ideas such as uncertainty, random experiments, sample spaces, and events. You’ll learn how to formally define probability and understand why it plays a central role in inferential statistics. The session also explains how to identify and represent outcomes of random experiments, helping you build a strong conceptual base for future lessons on conditional probability, independence, and statistical inference. This is the perfect starting point for mastering the logic behind probability theory. 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 #Probability #Statistics #RandomExperiment #SampleSpace #Events #Uncertainty #Math #Lecture #Tutorial #InferentialStatistics #DataScience #BasicProbability #ConditionalProbability #IndependentEvents #DependentEvents #QuantitativeMethods #StatisticalLearning #ProbabilityTheory #DataScienceEducation