Statistics for Data Science and Analytics (Wiley)
Monday, 07 October 2024

This guide to statistical analysis using Python presents important topics useful for data science such as prediction, correlation, and data exploration.Peter C. Bruce, Peter Gedeck and Janet Dobbins provide an introduction to statistical science and big data, as well as an overview of Python data structures and operations. A range of statistical techniques are presented with their implementation in Python, including hypothesis testing, probability, exploratory data analysis, categorical variables, surveys and sampling, A/B testing, and correlation.

<ASIN:139425380X>

The text introduces binary classification, a foundational element of machine learning, validation of statistical models by applying them to holdout data, and probability and inference via the easy-to-understand method of resampling and the bootstrap instead of using a myriad of “kitchen sink” formulas. Regression is taught both as a tool for explanation and for prediction

Author: Peter C. Bruce, Peter Gedeck and Janet Dobbins
Publisher: Wiley
Date: September 2024
Pages: 384
ISBN: 978-1394253807
Print: 139425380X
Kindle: B0DCGG7CHJ
Audience: Data scientists
Level: Intermediate
Category: Data Science and Python

Topics include:

  • Int, float, and string data types, numerical operations, manipulating strings, converting data types, and advanced data structures like lists, dictionaries, and sets
  • Experiment design via randomizing, blinding, and before-after pairing, as well as proportions and percents when handling binary data
  • Specialized Python packages like numpy, scipy, pandas, scikit-learn and statsmodels—the workhorses of data science—and how to get the most value from them
  • Statistical versus practical significance, random number generators, functions for code reuse, and binomial and normal probability distributions

For recommendations of books on data science see Reading Your Way Into Big Data in our Programmer's Bookshelf section.

For recommendations of Python books see Books for Pythonistas and Python Books For Beginners in our Programmer's Bookshelf section.

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