Welcome to Part 3 of my Statistics for Data Science and Analysis series!
In this video, we’re diving into probability distributions and how they apply to data analysis. From understanding discrete vs. continuous data to exploring key types of distributions—Bernoulli, Uniform, Binomial, Normal, Poisson, and Exponential—we'll cover it all in an easy-to-understand way.
You'll learn:
- What probability distributions are and why they matter.
- The difference between discrete and continuous distributions.
- Real-world examples and applications for each type.
- How knowing the distribution helps with statistical tests, model improvements, and more.
If you’ve ever wondered how probability shapes data analysis or how to choose the right tools for your dataset, this video is for you. Don't forget to check out Part 1 and Part 2 of the series (linked below).
Part 1: https://youtu.be/LdcDAfjlXFg?si=3UcTY6idnblaWtGM
Part 2: https://youtu.be/yvLxX9GAKTQ?si=k8ZFe6w3rSV8sv9E
CHAPTERS:
00:00 Intro
00:19 Definitions
01:05 Discrete vs Continuous Data
02:27 Bernoulli Distribution
03:31 Uniform Distribution
04:29 Binomial Distribution
05:55 Normal Distribution
07:04 Poisson Distribution
07:46 Exponential Distribution
08:27 Why is this important?
#datascience #dataanalysis #statistics