About the content
This course is part of the MITx MicroMasters program in Data, Economics, and Development Policy (DEDP). To enroll in the MicroMasters track or to learn more about this program and how it integrates with MIT’s Master’s Program in DEDP, please visit the MicroMasters portal.
The DEDP MicroMasters is part of edX’s free Online Campus program. Participating university affiliates can take DEDP MicroMasters courses free if you register before June 30th. If you are from a university participating in this edX opportunity,click here to redeem your coupon.
The DEDP MicroMasters is also part of the Workforce Recovery Acceleration Program. To apply for this program pleaseclick here.
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, includingwhy 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.
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 the this link to access the course preview.
- Designing a Randomized Evaluation
- Selecting a sample
- Measurement of outcomes
- Collecting and managing your data
- Research Integrity, Transparency, and Reproducibility
Although not required, prior familiarity with basic statistical concepts is recommended.
JPAL 102x – Designing and Running Randomized Evaluations
Week One: Introduction & Randomized Evaluation Design I
Week Two: Randomized Evaluation Design II
Week Three: Sampling and Sample Size
Week Four: Measurement I (Intro, Sensitive Topics, Market Activity)
Week Five: Measurement II (Welfare, Health, Networks)
Week Six: Measurement III (Behavior, Education, Gender and Empowerment)
Week Seven: Data Collection & Management I (Questionnaire Design)
Week Eight: Data Collection & Management II (Logistics and Monitoring)
Week Nine: Data Collection & Management III (Managing Data)
Week Ten: Research Integrity, Transparency, and Reproducibility I
Week Eleven: Research Integrity, Transparency, and Reproducibility II
Chief Economist, DFID; on leave from J-PAL
Massachusetts Institute of Technology
Director of Research, Education, & Training, J-PAL
Massachusetts Institute of Technology
MIT is a world-class educational institution where teaching and research — with relevance to the practical world as a guiding principle — continue to be its primary purpose.
MIT is independent, coeducational, and privately endowed. Its five schools and one college encompass numerous academic departments, divisions and degree-granting programs, as well as interdisciplinary centers, laboratories and programs whose work cuts across traditional departmental boundaries.
Harvard University, the Massachusetts Institute of Technology, and the University of California, Berkeley, are just some of the schools that you have at your fingertips with EdX. Through massive open online courses (MOOCs) from the world's best universities, you can develop your knowledge in literature, math, history, food and nutrition, and more. These online classes are taught by highly-regarded experts in the field. If you take a class on computer science through Harvard, you may be taught by David J. Malan, a senior lecturer on computer science at Harvard University for the School of Engineering and Applied Sciences. But there's not just one professor - you have access to the entire teaching staff, allowing you to receive feedback on assignments straight from the experts. Pursue a Verified Certificate to document your achievements and use your coursework for job and school applications, promotions, and more. EdX also works with top universities to conduct research, allowing them to learn more about learning. Using their findings, edX is able to provide students with the best and most effective courses, constantly enhancing the student experience.