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Designing and Running Randomized Evaluations

This course equips students with the practical skills for running evaluations in the field. Students will learn the foundations of randomizations and research design, as well as practical tips and skills for collecting high quality, reliable data in the field.

Designing and Running Randomized Evaluations

This course equips students with the practical skills for running evaluations in the field. Students will learn the foundations of randomizations and research design, as well as practical tips and skills for collecting high quality, reliable data in the field.

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**

A randomized evaluation, also known as a field experiment or randomized controlled trial (RCT), is an impact evaluation that uses random assignment to minimize bias, and strengthen our ability to draw causal inferences.

This course will provide step-by-step training on how to design and conduct an RCT. You will learn how to build a well-designed, policy relevant study, including why and when to conduct RCTs.

Additionally, this course will provide insights on how to implement your RCT in the field, including questionnaire design, piloting, quality control, data collection and management. The course will also introduce common research transparency practices.

No previous economics or statistics background is needed.

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.

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

  • Designing a Randomized Evaluation
  • Selecting a sample
  • Measurement of outcomes
  • Collecting and managing your data
  • Research Integrity, Transparency, and Reproducibility

Prerequisites

Although not required, prior familiarity with basic statistical concepts is recommended.

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 Rachel Glennerster
    Associate Professor of Economics at the University of Chicago

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.