Statistics for Data Science 1 - W8_L5: Discrete random variables - graph of probability mass function

Welcome to Week 8 Lecture 5 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 explores the Probability Mass Function (PMF) in depth. Beginning with a quick review of random variables, the session explains how PMFs assign probabilities to specific outcomes of discrete random variables. The lecture covers the properties of PMFs, how to verify if a function qualifies as a valid PMF, and methods to determine unknown constants within a PMF. We then move on to graphical representations of PMFs, learning how visualizing probability distributions helps in understanding their behavior. Examples such as dice rolls and coin tosses are used to illustrate these ideas, along with a brief introduction to the Cumulative Distribution Function (CDF). 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 #ProbabilityMassFunction #PMF #ProbabilityDistribution #DiscreteRandomVariable #Statistics #Probability #GraphingPMF #DiceRoll #CoinToss #CumulativeDistributionFunction #DataScience #StatisticalLearning #QuantitativeMethods #DataScienceEducation