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Sampling in Python

Intermediate
4.4+
68 reviews
Updated 12/2024
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 XP35,710Statement 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
Course
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*4.4
from 68 reviews
71%
15%
7%
3%
4%
  • PASCAL P.
    about 1 month

    Great course to learn sampling in Python.

  • muhammad t.
    3 months

    Great

  • Urich K.
    4 months

    Complex but very interesting

  • Noel C.
    5 months

    Excellent course! five stars

  • Li D.
    6 months

    Great course - a must. Very useful.

"Great course to learn sampling in Python."

PASCAL P.

"Great"

muhammad t.

"Complex but very interesting"

Urich K.

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