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Statistics I

School: Princeton University

Source: Coursera

Link: Statistics I

Start Date: Not Yet Available (Held in September 2013) 

Workload: 5-8 Hours A Week (12 Weeks Long)

Instructor: Andrew Conway

Credentials: Professor Conway, who joined Princeton’s faculty in 2004, teaches statistics to undergraduate and graduate students. A senior Lecturer in the Department of Psychology who is best known for his extensive research, Conway is the Principal Investigator at Princeton’s Human Working Memory Lab. He has published over 40 works in leading journals in Psychology and Neuroscience and serves as the Associate Editor for The Journal of Cognitive Psychology.

Graded: No certificates or statements are awarded for completing this course.

Description: This course provides a broad introduction to basic statistical concepts, such as research, correlation, measurement, regression, linear models, and t-tests.  It consists of 2 weekly lectures, and one weekly application lab. It relies heavily on the R programming language, with R software available free to students. Students are evaluated through weekly assignments, a midterm, and a final exam.

Review: “The first part of the course was great. At the end the pace was too fast. Has potential to be a great course in statistics.” To read additional reviews of this course, click here.

Additional Note: This is basically an undergraduate course. The University of California at Berkeley also offers a number of statistics courses via edX, while Stanford has collaborated with Udacity to provide Introduction To Statistics.

(See following pages for some of the best electives to consider)