Link to Content:

Coursera

Created/Published/Taught by:

Princeton University

Andrew Conway

Content Found Via:

Clare Corthell's Open Source Data Science Masters

Free?

Cost: $0.00

Tags: ANOVA / central limit theorem / correlation / generalized linear models / logistic regression / mutiple regression / R / statistics / t-test

Difficulty Rating:

Statistics One is not currently available from Coursera.

Statistics One is designed to be a comprehensive yet friendly introduction to fundamental concepts in statistics. Comprehensive means that this course provides a solid foundation for students planning to pursue more advanced courses in statistics. Friendly means exactly that. The course assumes very little background knowledge in statistics and introduces new concepts with several fun and easy to understand examples.

Statistics One also provides an introduction to the R programming language. All the examples and assignments will involve writing code in R and interpreting R output.

Every week will include two lectures and one lab. Lectures will cover theoretical concepts, whereas labs will present applied problems in R. In addition, your performance will be evaluated throughout the course with weekly assignments, as well as a midterm and final exam.

Recommended Prerequisites: Anyone and everyone is welcome to take this class. Proficiency in algebra is helpful but not necessary.

Go to Content: Statistics One

## By yissylevi December 23, 2015 - 10:22 am

I did this course more than two years ago and found it immensely helpful. I was a novice at statistics and this course really helped me gain a foothold in the concepts so that I could build on that knowledge. It also introduced me to R. It is a shame the Coursera no longer offers the course.

Early Beginner- new to data science / totally new to this topic / few prerequisitesEarly Beginner - was totally new to this topic / had few prerequisites

(5) More than I even wanted to!

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