**by Brian Caffo**

DescriptionTable of ContentsDetailsHashtagsReport an issue ### 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. ### Table of Contents

### Book Details

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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).

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

Publisher

Leanpub

Published

2016

Pages

124

Edition

1

Language

English

PDF Size

2.9 MB

License

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