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1
Intro
2
Notes
3
Random Sampling
4
Selection Bias
5
Regression to the Mean
6
Sampling Distributions
7
Sample Statistics
8
Lambda Functions
9
Illustrator Central Limit Theorem
10
Standard Error
11
Bootstrapping
12
Confidence Interval
13
Normal and Gaussian Distributions
14
Binomial Distribution
Description:
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.

Practical Statistics for Data Scientists - Data and Sampling Distributions

Shashank Kalanithi
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