Fundamentals of Data Science Part I: Inference and Experiment
Fundamentals of Data Science Part I: Inference and Experiment
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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
ISBN: 9781941043110
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