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

Introduction to Sampling

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

Sampling Methods

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.

Galat relatif dari taksiran titik

Menghitung galat relatif

Galat relatif vs. ukuran sampel

Membuat distribusi sampling

Mereplikasi sampel

Parameter replikasi

Perkiraan distribusi sampling

Distribusi sampling eksak

Membuat distribusi sampling pendekatan

Tepat vs. pendekatan

Galat baku dan Teorema Limit Pusat

Rata-rata populasi & distribusi sampling

Variasi populasi & distribusi sampling

Sampling 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!

Bootstrap Distributions

Coffee ratings

Spotify song attributes

Employee attrition

Sampling di Python adalah dasar dari statistika inferensial dan pengujian hipotesis. Ini merupakan keterampilan yang ampuh dalam analisis survei dan desain eksperimen untuk menarik kesimpulan tanpa mensurvei seluruh populasi. Dalam kursus Sampling di Python ini, Anda akan mempelajari kapan menggunakan sampling dan bagaimana melakukan jenis-jenis sampling umum—mulai dari sampling acak sederhana hingga metode yang lebih kompleks seperti sampling berstrata dan sampling klaster. Dengan menggunakan himpunan data dunia nyata, termasuk penilaian kopi, lagu Spotify, dan attrition karyawan, Anda akan belajar memperkirakan statistik populasi dan mengukur ketidakpastian pada perkiraan Anda dengan membuat distribusi sampling dan distribusi bootstrap.

Introduction to Statistics in Python

Belajar menarik kesimpulan dari data terbatas dengan Python dan statistik, termasuk berbagai teknik sampling.

Sampling di Python

Associate Data Scientist  dalam Python

Analis Data  dalam Python

Dasar-Dasar Statistik  dalam Python

Parameter replikasi

Sampling di Python

Latihan interaktif praktis