Statistics for Data Science 1 - W8_L4: Discrete random variables - probability mass function properties

Welcome to Week 8 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 Discrete Random Variables and explains how they are used to represent outcomes that take on a finite or countable number of distinct values. Using clear examples, we explore how Probability Mass Functions (PMFs) describe the probability associated with each possible value of a random variable. The lecture also discusses the key properties of PMFs, including how probabilities are distributed and how they must sum to one. Step by step examples are provided to strengthen understanding of PMFs and their role in 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 #RandomVariable #DiscreteRandomVariable #Probability #ProbabilityMassFunction #PMF #Statistics #DataScience #ProbabilityDistribution #QuantitativeMethods #StatisticalLearning #DataScienceEducation #ProbabilityConcepts #RandomVariablesExplained