Evaluating Impact in Low- and Middle-Income Countries from edX

Identifying effective policies is a process of trial and error, innovation and experimentation, success and failure. This course provides the basic scientific and statistical tools needed to identify whether a policy or program is generating impact. Organized into modules, the course covers topics ranging from the attribution problem to what is meant by statistical significance (margin of error) to the analysis of data generated by a randomized control trial. The course also helps answer practical questions related to impact evaluation, such as how large of a sample is needed and what can be done when compliance with an experimental design is imperfect or when data is missing for part of the sample.

This course was created collaboratively by Georgetown University and the World Bank's Strategic Impact Evaluation Fund with support from the Georgetown Center for New Designs in Learning and Scholarship, Georgetown University Initiative of Innovation, Development and Evaluation (gui2de), and The Open Learning Campus of the World Bank Group.

What you'll learn

Define impact evaluation and recognize its importance.
Describe the importance of randomization and the problems that can arise in randomized controlled trials (RCTs).
Identify statistical concepts and tools for program evaluation.
Interpret the concept of regression and how it informs RCT results.
Illustrate the balance between sample size and cost of trial.
Explain the value and application of quasi experimental methods

What's inside

Learning objectives

Define impact evaluation and recognize its importance.
Describe the importance of randomization and the problems that can arise in randomized controlled trials (rcts).
Identify statistical concepts and tools for program evaluation.

Interpret the concept of regression and how it informs rct results.
Illustrate the balance between sample size and cost of trial.
Explain the value and application of quasi experimental methods

Define impact evaluation and recognize its importance.
Describe the importance of randomization and the problems that can arise in randomized controlled trials (rcts).
Identify statistical concepts and tools for program evaluation.
Interpret the concept of regression and how it informs rct results.
Illustrate the balance between sample size and cost of trial.
Explain the value and application of quasi experimental methods

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Provides foundational grounding in the application of statistical concepts for evaluating program impact

Emphasizes the use of randomized controlled trials as a key methodology for impact evaluation

Guides learners through the identification of obstacles and measurement issues that may arise in conducting impact evaluations

Offers practical advice on strategies for navigating ethical dilemmas that may arise during impact evaluations

Reviews summary

Essential impact evaluation for development

Learners say this course provides a comprehensive and accessible introduction to impact evaluation, particularly for those working in low- and middle-income countries. Students consistently highlight the clarity of explanations for complex statistical concepts like RCTs and regression analysis, even for non-statisticians. The course is praised for its practical application focus, relevant real-world examples, and the expertise of its instructors. While it offers a strong theoretical foundation, some learners desired more hands-on software demonstrations for statistical analysis. A few found it challenging without a strong prior statistics background, suggesting it benefits those with at least intermediate statistical knowledge.

Instructors are knowledgeable and passionate.

"The instructors are clearly experts in their field and their passion for the subject shines through."

"The instructors are very knowledgeable and articulate."

"The instructors were excellent."

Builds a strong conceptual framework for impact evaluation.

"Overall a very solid course. It gives a good foundation in impact evaluation and introduces key concepts..."

"As someone new to impact evaluation, this course provided a comprehensive yet accessible introduction."

"It provided a solid conceptual understanding of impact evaluation."

Focuses on real-world applications in LMICs.

"The examples provided were highly relevant to real-world scenarios in low- and middle-income countries."

"The focus on LMICs is unique and highly relevant."

"I particularly appreciated the focus on practical application and the nuances of implementing evaluations in challenging environments."

Complex statistical concepts are made easy to grasp.

"The instructors explained complex statistical concepts like regression analysis and sample size determination in a way that was easy to understand..."

"The explanations of complex topics like RCTs and quasi-experimental methods were incredibly clear."

"I found it very accessible for someone new to the subject. The instructors simplify difficult concepts."

Beneficial for learners with some prior statistics knowledge.

"I found some parts a bit challenging to follow without a stronger background in statistics."

"I think it's better suited for someone with at least an intermediate grasp of statistics rather than a complete beginner."

"While they try to simplify it, some of the explanations for regression and statistical significance were still quite dense."

Some wished for more practical software demonstrations.

"I felt it could have included more hands-on exercises or software demonstrations for statistical analysis, especially for R or Stata..."

"Found this course to be too theoretical and not enough practical application. I came hoping to learn how to *do* impact evaluation with data..."

"I would have liked to see more practical assignments or a capstone project to apply the knowledge..."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Evaluating Impact in Low- and Middle-Income Countries with these activities:

Impact Evaluation Resource Compilation

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Build a repository of key resources and materials related to impact evaluation for future reference and ongoing learning.

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Identify and gather relevant articles, books, websites, and datasets
Organize and categorize materials by topic or theme
Create a bibliography or reference list for future use
Share your compilation with other learners or colleagues

Causal Inference in Statistics: A Primer

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Gain a solid theoretical foundation in statistical methods for causal inference, including randomization, matching, and regression analysis.

View Causal Inference in Statistics - A Primer on Amazon

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Read the chapters on randomized controlled trials and observational studies
Solve practice problems and case studies
Apply the concepts to your own research project

R for Impact Evaluation

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Enhance your data analysis skills by learning how to use R for data manipulation, statistical modeling, and impact evaluation.

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Complete the introductory tutorials on R basics
Learn how to import, clean, and manipulate data in R
Apply statistical methods to evaluate program impact using R packages
Create visualizations to communicate your findings

Five other activities

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Create a Python script that uses the pandas library to analyze data

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Build familiarity with Python and data analysis by following a guided tutorial on using the pandas library.

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Find a tutorial on using pandas for data analysis.
Follow the tutorial step-by-step.
Experiment with the code to explore different data analysis techniques.

Impact Evaluation Project

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Develop practical understanding of impact evaluation and apply statistical methods to assess the impact of a policy or program.

Browse courses on Program Evaluation

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Identify a policy or program to evaluate
Design a randomized controlled trial or quasi-experimental research design
Collect data and analyze results
Interpret findings and communicate results

Impact Evaluation Simulations

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Strengthen your understanding of impact evaluation methods through interactive simulations and exercises.

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Use online simulation tools to design and run randomized controlled trials
Analyze simulated data to estimate program effects
Evaluate the robustness of your findings under different scenarios
Discuss the implications of your findings for policy and practice

Impact Evaluation Discussion Group

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Engage with peers to discuss impact evaluation concepts, share experiences, and provide feedback on your work.

Browse courses on Collaborative Learning

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Join or create a study group
Participate in weekly discussions on assigned topics
Review and provide feedback on others' work
Collaborate on a group project related to impact evaluation

Policy Brief on Impact Evaluation Findings

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Condense your impact evaluation findings into a concise and accessible format for policymakers and stakeholders.

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Summarize the key findings of your impact evaluation
Identify the policy implications of your findings
Write a policy brief that clearly communicates your findings and recommendations
Disseminate your policy brief to relevant policymakers and stakeholders

Career center

Learners who complete Evaluating Impact in Low- and Middle-Income Countries will develop knowledge and skills that may be useful to these careers:

Impact Evaluation Specialist

Impact Evaluation Specialists design and implement impact evaluations to assess the effectiveness of programs and policies. They use statistical methods to analyze data and provide evidence-based recommendations. The course, Evaluating Impact in Low- and Middle-Income Countries, was specifically designed for this career role. It provides training in the design and implementation of impact evaluations, including the use of randomized controlled trials.

See salaries and explore the career path for Impact Evaluation Specialist

Statistician

Statisticians use statistical methods to collect, analyze, interpret, and present data. They work in a variety of fields, including healthcare, finance, and marketing. The course, Evaluating Impact in Low- and Middle-Income Countries, provides training in the core statistical methods used by statisticians in all fields.

See salaries and explore the career path for Statistician

Data Scientist

Data Scientists apply scientific methods, processes, algorithms, and systems to extract knowledge and insights from data. They analyze and interpret large volumes of data to find correlations between data points. The course, Evaluating Impact in Low- and Middle-Income Countries, provides a solid foundation in statistical modeling, econometrics and causal inference, all of which are core scientific methods used in data science. Anyone who wishes to be a Data Scientist would benefit from taking this course.

See salaries and explore the career path for Data Scientist

Policy Analyst

Policy Analysts develop and evaluate policies to address public issues. They use research methods to collect and analyze data to inform policy decisions. The course, Evaluating Impact in Low- and Middle-Income Countries, provides training in the methods used by policy analysts, such as data analysis and statistical modeling.

See salaries and explore the career path for Policy Analyst

Business Analyst

Business Analysts use data to analyze business processes and make recommendations for improvement. They work in a variety of industries, including consulting and finance. The course, Evaluating Impact in Low- and Middle-Income Countries, provides training in the data analysis methods used by business analysts.

See salaries and explore the career path for Business Analyst

Program Evaluator

Program Evaluators assess the effectiveness of programs and policies. They use research methods to collect and analyze data to determine whether programs are achieving their objectives. The course, Evaluating Impact in Low- and Middle-Income Countries, while not specifically tailored to program evaluation, does help to develop the core skills that are necessary for success in this role, such as data analysis and statistical modeling.

See salaries and explore the career path for Program Evaluator

Data Analyst

Data Analysts use data to solve business problems. They collect, clean, and analyze data to identify trends and patterns. The course, Evaluating Impact in Low- and Middle-Income Countries, provides training in the data analysis methods used by data analysts.

See salaries and explore the career path for Data Analyst

Health Economist

Health Economists use economic principles to analyze the healthcare system. They work in a variety of settings, including government and academia. The course, Evaluating Impact in Low- and Middle-Income Countries, provides training in the statistical methods used by health economists.

See salaries and explore the career path for Health Economist

Research Scientist

Research Scientists conduct research to advance knowledge in various scientific fields. They use scientific methods to design and conduct experiments, collect and analyze data, and draw conclusions. The course, Evaluating Impact in Low- and Middle-Income Countries, builds a foundation in statistical methods and causal inference, which are used by Research Scientists in a variety of fields.

See salaries and explore the career path for Research Scientist

Actuary

Actuaries use mathematical and statistical methods to assess risk and uncertainty. They work in a variety of industries, including insurance and finance. The course, Evaluating Impact in Low- and Middle-Income Countries, provides training in the statistical methods used by actuaries to assess risk.

See salaries and explore the career path for Actuary

Quantitative Analyst

Quantitative Analysts use mathematical and statistical methods to analyze data and make predictions. They work in a variety of fields, including finance and trading. The course, Evaluating Impact in Low- and Middle-Income Countries, provides training in the statistical methods used by quantitative analysts.

See salaries and explore the career path for Quantitative Analyst

Operations Research Analyst

Operations Research Analysts use mathematical and statistical methods to solve problems in business and industry. They work in a variety of industries, including manufacturing and logistics. The course, Evaluating Impact in Low- and Middle-Income Countries, provides training in the statistical methods used by operations research analysts.

See salaries and explore the career path for Operations Research Analyst

Risk Analyst

Risk Analysts use statistical methods to assess risk and uncertainty. They work in a variety of industries, including finance and insurance. The course, Evaluating Impact in Low- and Middle-Income Countries, provides training in the statistical methods used by risk analysts.

See salaries and explore the career path for Risk Analyst

Financial Analyst

Financial Analysts use financial data to make investment recommendations. They work in a variety of industries, including banking and investment management. The course, Evaluating Impact in Low- and Middle-Income Countries, provides training in the statistical methods used by financial analysts.

See salaries and explore the career path for Financial Analyst

Market Research Analyst

Market Research Analysts gather data on marketing campaigns to determine the effectiveness of campaigns and make improvements in the future. They rely on statistical data and analysis to understand marketing data. The course, Evaluating Impact in Low- and Middle-Income Countries, may be useful for those in this role, because it provides training in statistical analysis, which would aid the analyst in working with complex datasets.

See salaries and explore the career path for Market Research Analyst