课程

Python 抽样

中级技能水平

更新时间 2025年1月

学会用 Python 和统计学从有限数据中得出结论。本课程涵盖从随机抽样到分层抽样和整群抽样的所有内容。

免费开始课程

PythonProbability & Statistics

4小时

15 视频

51 道练习

4,000 XP

53,890

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课程描述

Python 抽样是推断统计和假设检验的基石。它是一项强大的技能，常用于调查分析和实验设计，帮助您在不对整体进行全面调查的情况下得出结论。在本课程 Python 抽样中，您将了解何时使用抽样，以及如何执行常见的抽样方法——从简单随机抽样到更复杂的分层抽样和整群抽样。借助真实世界的数据集（包括咖啡评分、Spotify 歌曲和员工流失数据），您将学习如何估计总体统计量，并通过生成抽样分布和自助法分布来量化估计的不确定性。

先决条件

Introduction to Statistics in Python

1

Introduction to Sampling

Learn what sampling is and why it is so powerful. You’ll also learn about the problems caused by convenience sampling and the differences between true randomness and pseudo-randomness.

Sampling and point estimates

Reasons for sampling

Simple sampling with pandas

Simple sampling and calculating with NumPy

Convenience sampling

Are findings from the sample generalizable?

Are these findings generalizable?

Pseudo-random number generation

Generating random numbers

Understanding random seeds

2

Sampling Methods

It’s time to get hands-on and perform the four random sampling methods in Python: simple, systematic, stratified, and cluster.

Simple random and systematic sampling

Simple random sampling

Systematic sampling

Is systematic sampling OK?

Stratified and weighted random sampling

Which sampling method?

Proportional stratified sampling

Equal counts stratified sampling

Weighted sampling

Cluster sampling

Benefits of clustering

Performing cluster sampling

Comparing sampling methods

3 kinds of sampling

Comparing point estimates

3

Sampling Distributions

Let’s test your sampling. In this chapter, you’ll discover how to quantify the accuracy of sample statistics using relative errors, and measure variation in your estimates by generating sampling distributions.

Relative error of point estimates

Calculating relative errors

Relative error vs. sample size

Creating a sampling distribution

Replicating samples

Replication parameters

Approximate sampling distributions

Exact sampling distribution

Generating an approximate sampling distribution

Exact vs. approximate

Standard errors and the Central Limit Theorem

Population & sampling distribution means

Population & sampling distribution variation

4

Bootstrap Distributions

You’ll get to grips with resampling to perform bootstrapping and estimate variation in an unknown population. You’ll learn the difference between sampling distributions and bootstrap distributions using resampling.

Introduction to bootstrapping

Principles of bootstrapping

With or without replacement?

Generating a bootstrap distribution

Comparing sampling and bootstrap distributions

Bootstrap statistics and population statistics

Sampling distribution vs. bootstrap distribution

Compare sampling and bootstrap means

Compare sampling and bootstrap standard deviations

Confidence intervals

Confidence interval interpretation

Calculating confidence intervals

Congratulations!

Python 抽样

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