.

You don't have to take college classes to learn statistics. If you just want some basic information about a particular statistical topic, then StatisticsHowTo.com is a great way to start. But if you're looking for more structured training and perhaps a certification, you've got a lot of good options.

## Beginner Statistics Resources

If you have zero to little statistics or programming knowledge, these resources give you the basics without coding:

My personal favorite: The Open University's Open Learn resource (The OU is where I started my college career). You can access a wide range of high quality courses for free from a long established British university, including:

What I love best about the OU is that is assumes zero prior experience. If you need help with a more basic topic, then they have courses on those too, from working a scientific calculator to an introduction to complex numbers.

The BMJ's book Statistics at Square One is accessible online in its entirety. You don't need to sign up for an account. The book has been revised many times since it's publication (the online version is the original), so if you're willing to put up with an error here and there, this is a great resource.

MIT's Open Courseware has a plethora of probability and statistics courses listed, including this one on Statistical Thinking and Data Analysis.

Udacity's Intro to Descriptive Statistics. This 2 month course covers what you would expect to learn in the first few weeks of a college statistics class, including variability and normal distributions. Udacity also offers a 2 month course titled Intro to Inferential Statistics. Although they state that it's a beginner level, in order to be comfortable with the material you should have some exposure to basic statistical concepts (like those covered in Udacity's Intro course).

## Programming and Data Science

If you want to add on some statistics knowledge and you're comfortable programming, then these resources are for you.

SAS users can opt for a beginner class called Statistics 1: Introduction to ANOVA, Regression, and Logistic Regre... Although it's a beginner class, it's aimed at SAS users, so some analytical knowledge is assumed.

For Python programmers:

• Think Stats, an introduction to Probability and Statistics is based on a Python library for probability distributions (PMFs and CDFs). Free PDF and online versions are available under a Creative Commons license. If you like the introductory book and want to dive into Bayesian probability, then a follow up is available: Think Bayes.
• Probability and Statistics in Data Science Using Python is a free course from edX presented by instructors from UC San Diego.

Interested in learning R? An Introduction to Statistical Learning is now in its 7th edition and is available as a free PDF.

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