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10 FREE Resources to Learn Statistics

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Learning statistics is a very important step on the path to becoming a data scientist. It is not an easy subject and many people are often off-put by the complex and convoluted explanations. Luckily, more and more easy to digest tutorials, ebooks and courses become available on the internet. Here is a small selection to get you started.

1. Elementary Statistics with R (ebook)

An e-book providing simple solutions to common statistical problems. Covers topics ranging from basic probability distributions, estimation, hypothesis testing to regression models. Provides only basic theory.

2. Introduction to Statistical Thought (ebook)

This material places strong emphasis on key ideas behind statistical procedures and less emphasis on technical details. A very good self-study book for people who like to understand Why.

3. Online Statistics Education: An Interactive Multimedia Course of Study (ebook)

An interesting website/ebook with interactive java applets to play with. The typesetting is not always great (even in the PDF format).

4. The Elements of Statistical Learning (ebook)

A statistics bible that sits somewhere between hard theoretical material and machine learning. Contains detailed descriptions of linear regression, classification models, kernel methods, bootstrapping, trees, neural networks and SVMs. Great for a more advanced reader.

5. Introduction to Probability and Statistics Using R (ebook)

Ebook coupled with an R package. Make sure you check the INSTALLATION file as this ebook need to be opened through R (install the IPSUR package from CRAN and call “read(IPSUR)” to open the PDF). Good theory and a lot of examples. Areas covered include probability theory, distributions, hypothesis testing and regression.

6. OpenIntro Statistics (ebook)

Covers the standard array of subjects (distributions, testing, regression), but includes many examples and exercises. Nicely typeset with a text-book feel.

7. Statistics One (course)

One of the most popular courses on Coursera. Topics covered include the standard summary statistics, hypothesis testing, linear regression, GLM and ANOVA. Highly recommended.

8. Statistics: Making Sense of Data (course)

A basic and easy to understand introductory course in statistical data analysis. Covers methods of data collection, constructing graphical displays to understand the data, estimating errors and key ideas on how to use statistical tests.

9. Statistics 101 by Brandon Foltz (video playlist)

A selection of introductory lectures – easy to follow and aimed at people with no background in statistics.

10. Statistics 110 from Harvard University (video playlist)

A full lecture in advanced statistics from the Harvard University. Highly technical at times and mostly recommended for people with good math background.

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