Statistical inference for data science
A companion to the Coursera Statistical Inference Course
by Brian Caffo
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Book Description
The ideal reader for this book will be quantitatively literate and has a basic understanding of statistical concepts and R programming. The book gives a rigorous treatment of the elementary concepts in statistical inference from a classical frequentist perspective. After reading this book and performing the exercises, the student will understand the basics of hypothesis testing, confidence intervals and probability.This open book is licensed under a Creative Commons License (CC BY-NC-SA). You can download Statistical inference for data science ebook for free in PDF format (2.9 MB).
Table of Contents
Chapter 1
Introduction
Chapter 2
Probability
Chapter 3
Conditional probability
Chapter 4
Expected values
Chapter 5
Variation
Chapter 6
Some common distributions
Chapter 7
Asymptopia
Chapter 8
t Confidence intervals
Chapter 9
Hypothesis testing
Chapter 10
P-values
Chapter 11
Power
Chapter 12
The bootstrap and resampling
Book Details
Title
Statistical inference for data science
Publisher
Leanpub
Published
2016
Pages
124
Edition
1
Language
English
PDF Size
2.9 MB
License
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