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Sampling in Python

James Chapman

Curriculum Manager, DataCamp

Recap

Chapter 1

  • Sampling basics
  • Selection bias
  • Pseudo-random numbers

Chapter 3

  • Sample size and population parameters
  • Creating sampling distributions
  • Approximate vs. actual sampling dist'ns
  • Central limit theorem

Chapter 2

  • Simple random sampling
  • Systematic sampling
  • Stratified sampling
  • Cluster sampling

Chapter 4

  • Bootstrapping from a single sample
  • Standard error
  • Confidence intervals
Sampling in Python

The most important things

 

  • The std. deviation of a bootstrap statistic is a good approximation of the standard error
  • Can assume bootstrap distributions are normally distributed for confidence intervals
Sampling in Python

What's next?

Sampling in Python

Happy learning!

Sampling in Python

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