Practical Statistics for Data Scientists - Data and Sampling Distributions

Explore the fundamentals of data and sampling distributions in this comprehensive video overview of Chapter 2 from "Practical Statistics for Data Scientists." Delve into key concepts such as random sampling, selection bias, regression to the mean, and sampling distributions. Learn about sample statistics, lambda functions, and the Central Limit Theorem. Gain insights into standard error, bootstrapping, confidence intervals, and various probability distributions including Normal, Gaussian, and Binomial. Master essential statistical principles crucial for data science applications through this informative 56-minute lecture by Shashank Kalanithi.

Intro
Notes
Random Sampling
Selection Bias
Regression to the Mean
Sampling Distributions
Sample Statistics
Lambda Functions
Illustrator Central Limit Theorem
Standard Error
Bootstrapping
Confidence Interval
Normal and Gaussian Distributions
Binomial Distribution