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Sampling in Python

Intermediate
4.7+
832 reviews
Updated 04/2025
Learn to draw conclusions from limited data using Python and statistics. This course covers everything from random sampling to stratified and cluster sampling.
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PythonProbability & Statistics4 hours15 videos51 Exercises4,000 XP40,313Statement of Accomplishment

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Course Description

Sampling in Python is the cornerstone of inference statistics and hypothesis testing. It's a powerful skill used in survey analysis and experimental design to draw conclusions without surveying an entire population. In this Sampling in Python course, you’ll discover when to use sampling and how to perform common types of sampling—from simple random sampling to more complex methods like stratified and cluster sampling. Using real-world datasets, including coffee ratings, Spotify songs, and employee attrition, you’ll learn to estimate population statistics and quantify uncertainty in your estimates by generating sampling distributions and bootstrap distributions.

Prerequisites

Introduction to Statistics in Python
1

Introduction to Sampling

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2

Sampling Methods

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3

Sampling Distributions

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4

Bootstrap Distributions

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Sampling in Python
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*4.7
from 832 reviews
78%
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2%
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  • Masahiro
    about 13 hours

    This course take you through sampling methods and bootstrapping with examples, which helped me understanding ideas of those methods really well. Exciting experience!

  • Ethan
    about 15 hours

  • Brayden
    about 21 hours

  • Paige
    about 21 hours

  • Luis
    about 22 hours

  • Ahmed
    about 20 hours

"This course take you through sampling methods and bootstrapping with examples, which helped me understanding ideas of those methods really well. Exciting experience!"

Masahiro

Ethan

Brayden

    Join over 16 million learners and start Sampling in Python today!

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