Welcome to this comprehensive lecture on Continuous Random Variables!
In this video, we cover the foundations of continuous probability distributions, including definitions, probability density functions (PDF), cumulative distribution functions (CDF), uniform distributions, probability calculations, percentiles, expected values, and hands-on examples with Python using Scipy and Matplotlib.
📌 Whether you're working on probabilistic modeling or preparing for interviews, this video builds a strong theoretical foundation with hands-on coding using Scipy and Matplotlib.
🖥️ Code and resources available in the description.
💬 Have questions? Drop them in the comments below!
🔔 Topics Covered:
Basics and Definitions
Probability Density Function (PDF)
Cumulative Distribution Function (CDF)
Uniform Distribution
Probabilities and Percentiles
Expected Values
Examples and Python Coding with Scipy and Matplotlib
📌 Whether you're working on probabilistic modeling or preparing for interviews, this video builds a strong theoretical foundation with hands-on coding using Scipy and Matplotlib.
🖥️ Code and resources available in the description.
💬 Have questions? Drop them in the comments below!
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