Fundamentals of Data Science Part I: Inference and Experiment


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Description

In Part I of this series, we cover basic statistical inference and experimentation, focusing on:

  • basic statistics;
  • derivation and review of key distributions and their relations;
  • hypothesis testing, including an in depth power analysis for the chi-squared statistic;
  • experimentation, including A/B tests, stratification, one- and two-factor experiments, and an introduction to bandit algorithms;
  • maximum likelihood;
  • gradient descent;
  • introduction to survival analysis and stochastic processes, including empirical estimation of online survival and event processes.

The theory is illustrated with simulations in Python throughout the text.



Author: Jared M. Maruskin
Publisher: Cayenne Canyon Press
Published: 04/30/2021
Pages: 314
Binding Type: Paperback
Weight: 0.97lbs
Size: 9.21h x 6.14w x 0.66d
ISBN13: 9781941043110
ISBN10: 1941043119
BISAC Categories:
- Mathematics | Probability & Statistics | General
- Computers | Data Science | General

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