## Book description

Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.

Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.

With this book, you’ll learn:

- Why exploratory data analysis is a key preliminary step in data science
- How random sampling can reduce bias and yield a higher quality dataset, even with big data
- How the principles of experimental design yield definitive answers to questions
- How to use regression to estimate outcomes and detect anomalies
- Key classification techniques for predicting which categories a record belongs to
- Statistical machine learning methods that “learn” from data
- Unsupervised learning methods for extracting meaning from unlabeled data

## Publisher resources

## Table of contents

- Preface
- 1. Exploratory Data Analysis
- 2. Data and Sampling Distributions
- 3. Statistical Experiments and Significance Testing
- 4. Regression and Prediction
- 5. Classification
- 6. Statistical Machine Learning
- 7. Unsupervised Learning
- Bibliography
- Index

## Product information

- Title: Practical Statistics for Data Scientists
- Author(s):
- Release date: May 2017
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781491952962

## You might also like

book

### Practical Statistics for Data Scientists, 2nd Edition

Statistical methods are a key part of data science, yet few data scientists have formal statistical …

video

### Statistics for Data Science and Business Analysis

This course will teach you fundamental skills that will enable you to understand complicated statistical analysis …

book

### Essential Math for Data Science

Master the math needed to excel in data science, machine learning, and statistics. In this book …

book

### Think Like a Data Scientist

Think Like a Data Scientist presents a step-by-step approach to data science, combining analytic, programming, and …