One of the best-known books on statistics is now free

Larry Wasserman’s All of Statistics is free to download from Springer

I like this book because – unlike most books on statistics - it takes a modern approach to statistics and covers statistics and computer science holistically.

In doing so, it covers a much broader range of topics (hence the name).

However, the book is also quite readable because the author says ‘Rigor and clarity are not synonymous’

Hence, it strikes a good balance

**Part I** is concerned with probability theory

**Part II** is about statistical inference, data mining and machine learning.

Part III applies the ideas from Part II to specific problems such as regression, graphical models, causation, density estimation, smoothing, classification, and simulation.

Admittedly, seeing everything in terms of statistics needs some getting used to

For example:

- Regression is a method for studying the relationship between a response variable Y and a covariate X. The covariate is also called a predictor variable or a feature. One way to summarize the relationship between X and Y is through the regression function

- Classification can be seen as the problem of predicting a discrete random variable Y from another random variable X
- Gaussian and Linear Classifiers : Gaussian and Linear Classifiers use the density estimation strategy and assume a parametric model for the densities.
- Trees are classification methods that partition the covariate space X into disjoint pieces and then classify the observations according to which partition element they fall in.

Etc etc …

The link again to download is

© 2020 TechTarget, Inc. Powered by

Badges | Report an Issue | Privacy Policy | Terms of Service

**Most Popular Content on DSC**

To not miss this type of content in the future, subscribe to our newsletter.

- Book: Applied Stochastic Processes
- Long-range Correlations in Time Series: Modeling, Testing, Case Study
- How to Automatically Determine the Number of Clusters in your Data
- New Machine Learning Cheat Sheet | Old one
- Confidence Intervals Without Pain - With Resampling
- Advanced Machine Learning with Basic Excel
- New Perspectives on Statistical Distributions and Deep Learning
- Fascinating New Results in the Theory of Randomness
- Fast Combinatorial Feature Selection

**Other popular resources**

- Comprehensive Repository of Data Science and ML Resources
- Statistical Concepts Explained in Simple English
- Machine Learning Concepts Explained in One Picture
- 100 Data Science Interview Questions and Answers
- Cheat Sheets | Curated Articles | Search | Jobs | Courses
- Post a Blog | Forum Questions | Books | Salaries | News

**Archives:** 2008-2014 |
2015-2016 |
2017-2019 |
Book 1 |
Book 2 |
More

**Most popular articles**

- Free Book and Resources for DSC Members
- New Perspectives on Statistical Distributions and Deep Learning
- Time series, Growth Modeling and Data Science Wizardy
- Statistical Concepts Explained in Simple English
- Machine Learning Concepts Explained in One Picture
- Comprehensive Repository of Data Science and ML Resources
- Advanced Machine Learning with Basic Excel
- Difference between ML, Data Science, AI, Deep Learning, and Statistics
- Selected Business Analytics, Data Science and ML articles
- How to Automatically Determine the Number of Clusters in your Data
- Fascinating New Results in the Theory of Randomness
- Hire a Data Scientist | Search DSC | Find a Job
- Post a Blog | Forum Questions

## You need to be a member of Data Science Central to add comments!

Join Data Science Central