Practical Statistics for Data Scientists: 50 Essential Concepts
Download e-Book
Book Introduction
e-Books Highlight
-
Edition1st Edition
-
ISBNB071NVDFD6
-
Posted on2017-05-15
-
FormatPdf
-
Page Count292 Pages
-
Author
About the e-Book
Practical Statistics for Data Scientists: 50 Essential Concepts Pdf
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
This site comply with DMCA digital copyright. We do not store files not owned by us, or without the permission of the owner. We also do not have links that lead to sites DMCA copyright infringement.
If You feel that this book is belong to you and you want to unpublish it, Please Contact us .
By Libribook
iOS Apps with REST APIs
The Algorithmic Fungus