Preparing for the training

To make the most of this training, participants will benefit from having some basic knowledge of randomized evaluations and familiarity with basic statistics. However, we recognize that participants come from varying technical and academic backgrounds, and we are committed to ensuring that everyone has the resources needed to succeed.

If you would like to review or strengthen your background in any of these areas before the training, we recommend the following resources:

• Randomized Evaluations 101:  

  • RCT 101x: Evaluating Social Programs: This is a self-paced, online version of our flagship in-person training course, and focuses on why and when randomized evaluations can be used to rigorously measure the impact of social programs. It is available in three languages and takes an average of 10-16 hours to complete. All participants will gain access to these instructions for accessing the course after registering.

  • J-PAL Introduction to Randomized Evaluations: This resource gives an overview and non-technical introduction to randomized evaluations. The section Teaching resources on randomized evaluations includes recorded lectures and other material from previous iterations of J-PAL's Evaluating Social Programs course.   

• Getting started with Stata/R: 

  • IPA's Stata Trainings: You will need access to Stata 16, 17, 18, or 19 to complete these exercises. The courses vary in difficulty and skill level. To determine the best starting point for you, you can take this test to assess which level you should begin with, or refer to the Stata Level Information Page.

Stata 101 Stata 102 Stata 103 Stata 104 Stata 201

• • R, R Studio, Swirl: Anyone interested in learning R should complete the installation instructions found here. This process takes approximately 20-30 minutes with decent internet speed. You can take the same diagnostic test linked above to assess which level you should begin with.

14_310x Intro to R 14_310x Advanced R

• Foundational Statistics: 

  • Khan Academy Statistics and Probability: This is a free online course on Statistics and Probability. Units 3–6 and 11–12 will be most relevant to the Research Staff Training

  • MIT OpenCourseWare: For a deeper dive, MIT OCW hosts material from its Spring 2022 undergraduate Introduction to Statistics and Probability. A compilation of the Statistics readings can be found here. Please note, this is provided only if you're interested in exploring the topic further. You do NOT need to learn this material to participate in RST.

We are dedicated to supporting all participants in their learning journey. If you have any concerns about preparation or require accommodations to fully engage in the training, please let us know—we will do our best to provide the necessary support.