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Statistics for the Social Sciences

by Duke Sociology

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Description

Taught by Brad Fulton, this course provides an introduction to the quantitative methods social scientists use to collect and evaluate empirical data about society. Lecture slides can be accessed at: http://sites.duke.edu/fulton/stats/. Students will learn to gather, describe, and analyze data with an emphasis on the application and interpretation of these methods. This course incorporates data from the General Social Survey to enable students to analyze characteristics, behaviors, and trends of the U.S. population. It will also help students be more informed and critical readers of academic research, public opinion polling, and advertisement claims that present statistical evidence. While the techniques are quantitative, little mathematical experience is required. Sociology at Duke provides the opportunity to explore any and all aspects of society, from the most narrowly individual to the most sweeping comparisons across civilizations. Sociology at Duke provides the opportunity to explore any and all aspects of society, from the most narrowly individual to the most sweeping comparisons across civilizations.

Customer Reviews

Associate Professor of Sociology

Great course! This course provided an excellent template and approach as I prepared to teach my version of Intro to Statistics.
The innovative bootstrapping approach provides an intuitive understanding of statistics.
Course is well-designed and well thought-out all the way through -- truly excellent!

Very Helpful

Wow, this course is very clear and easy to understand. This course is very complete, one of the things I enjoy is using the GSS website. This is a great free course with an excellent instructor, I recommend this course to anyone that wants to learn and understand the science of statistics for the behavioral sciences.

Assistant Professor in Sociology

I really enjoyed how the class was taught and was inspired to use the same book!

I particularly liked using bootstrapping and randomization distributions to understand sampling distributions, standard errors, and hypothesis testing. If you teach students these concepts early, then they more intuitive which benefits students in the long run.