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Data Analysis for Social Scientists

Learn methods for harnessing and analyzing data to answer questions of cultural, social, economic, and policy interest.

Data Analysis for Social Scientists

Learn methods for harnessing and analyzing data to answer questions of cultural, social, economic, and policy interest.

The course is free to audit. Learners can take a proctored exam and earn a course certificate by paying a fee, which varies by ability to pay. Please scroll down for more information on the verified and audit track features and see FAQ articles for more information on the pricing structure. Enroll now in this course by selecting the "enroll now" button at the top of the page.

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This is a CORE course within the MITx MicroMasters program in Data, Economics, and Design of Policy (DEDP), which provides a path toward the Master’s in DEDP at MIT.

** Three CORE courses are needed to complete the MicroMasters Program Credential in DEDP. For more information on DEDP MicroMasters program requirements, please visit our FAQ page**

This statistics and data analysis course will introduce you to the essential notions of probability and statistics. We will cover techniques in modern data analysis: estimation, regression and econometrics, prediction, experimental design, randomized control trials (and A/B testing), machine learning, and data visualization. We will illustrate these concepts with applications drawn from real world examples and frontier research. Finally, we will provide instruction for how to use the statistical package R and opportunities for students to perform self-directed empirical analyses.

This course is designed for anyone who wants to learn how to work with data and communicate data-driven findings effectively.

Course Previews:

Our course previews are meant to give prospective learners the opportunity to get a taste of the content and exercises that will be covered in each course. If you are new to these subjects, or eager to refresh your memory, each course preview also includes some available resources. These resources may also be useful to refer to over the course of the semester.

A score of 60% or above in the course previews indicates that you are ready to take the course, while a score below 60% indicates that you should further review the concepts covered before beginning the course.

Please use this link to access the syllabus and this link to access the course preview. Once you have completed this preview, use the answer key to check your answers.

Comparing the Audit and Certificate Tracks

Image is of a table explaining the different features of the verified and audit track. For an text table please use the link below.

(Click here for a text based version of this table.)

What you'll learn

  • Intuition behind probability and statistical analysis
  • How to summarize and describe data
  • A basic understanding of various methods of evaluating social programs
  • How to present results in a compelling and truthful way
  • Skills and tools for using R for data analysis

Prerequisites

No prior preparation in probability and statistics is required, but familiarity with algebra and calculus is assumed.

Meet your instructors

  • Featured image for Esther Duflo
    Abdul Latif Jameel Professor of Poverty Alleviation and Development Economics in the Department of Economics
  • Featured image for Sara Fisher Ellison
    Senior Lecturer

Who can take this course?

Because of U.S. Office of Foreign Assets Control (OFAC) restrictions and other U.S. federal regulations, learners residing in one or more of the following countries or regions will not be able to register for this course: Iran, Cuba, Syria, North Korea and the Crimea, Donetsk People's Republic and Luhansk People's Republic regions of Ukraine.