W4_L5: Probability density function | definition properties & examples

Welcome to Week 4 Lecture 5 of the course "Statistics for Data Science - II" by Prof. Andrew Thangaraj Full Course: https://study.iitm.ac.in/ds/course_pa... Video Overview This lecture introduces probability density functions PDFs for continuous random variables. We explain why PDFs are necessary for continuous data and compare them with probability mass functions PMFs for discrete variables. After a short integration refresher we define the PDF explore its relationship with the cumulative distribution function CDF and show why PDFs are intuitive and useful for probability calculations. Examples illustrate how to verify a valid PDF and calculate probabilities using integration. 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/stud... #ContinuousRandomVariables #ProbabilityDensityFunction #PDF #CumulativeDistributionFunction #CDF #Probability #Statistics #Integration #Calculus #DataScience #RandomVariables #DistributionFunction #Math #ProbabilityCalculations #DensityFunction #IITMadras #onlinedegree