We may earn an affiliate commission when you visit our partners.
Course image
Alaka Holla

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.

Read more

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

Here's a deal for you

We found an offer that may be relevant to this course.
Save money when you learn. All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.

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

Good to know

Know what's good
, what to watch for
, 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

Save this course

Save Evaluating Impact in Low- and Middle-Income Countries to your list so you can find it easily later:
Save

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
Build a repository of key resources and materials related to impact evaluation for future reference and ongoing learning.
Browse courses on Resource Management
Show steps
  • 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
Gain a solid theoretical foundation in statistical methods for causal inference, including randomization, matching, and regression analysis.
Show steps
  • 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
Enhance your data analysis skills by learning how to use R for data manipulation, statistical modeling, and impact evaluation.
Browse courses on Data Analysis
Show steps
  • 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
Expand to see all activities and additional details
Show all eight activities
Create a Python script that uses the pandas library to analyze data
Build familiarity with Python and data analysis by following a guided tutorial on using the pandas library.
Browse courses on Python
Show steps
  • 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
Develop practical understanding of impact evaluation and apply statistical methods to assess the impact of a policy or program.
Browse courses on Program Evaluation
Show steps
  • 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
Strengthen your understanding of impact evaluation methods through interactive simulations and exercises.
Browse courses on Case Studies
Show steps
  • 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
Engage with peers to discuss impact evaluation concepts, share experiences, and provide feedback on your work.
Browse courses on Collaborative Learning
Show steps
  • 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
Condense your impact evaluation findings into a concise and accessible format for policymakers and stakeholders.
Browse courses on Policy Analysis
Show steps
  • 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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.

Reading list

We've selected 11 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Evaluating Impact in Low- and Middle-Income Countries.
Provides a comprehensive overview of social and behavioral research methods. It valuable resource for students, researchers, and practitioners.
This handbook on experimental political science provides a valuable source of information for students, researchers, and practitioners.
This handbook on public policy provides a valuable source of information for students, researchers, and practitioners.
Provides a practical guide to impact evaluation. It valuable resource for anyone interested in learning more about how to design and implement impact evaluations.
Provides a comprehensive overview of regression analysis methods. It valuable resource for students, researchers, and practitioners.
Provides a comprehensive introduction to causal inference. It valuable resource for learners who want to learn more about the theoretical foundations of impact evaluation.
Popular textbook on econometrics. It provides a clear and concise introduction to the econometric methods used in impact evaluation.
Provides a comprehensive overview of quasi-experimental design methods. It valuable resource for students, researchers, and practitioners.
Provides an accessible introduction to research design and causality. It valuable resource for learners who are new to impact evaluation.
Provides a concise overview of impact evaluation for development. It valuable resource for learners who are new to impact evaluation and who are interested in learning more about the different methods and approaches used in impact evaluation.

Share

Help others find this course page by sharing it with your friends and followers:

Similar courses

Here are nine courses similar to Evaluating Impact in Low- and Middle-Income Countries.
Impact Evaluation Methods with Applications in Low- and...
Most relevant
Evaluation of Digital Health Interventions
Most relevant
Advanced Statistical Inference and Modelling Using R
Most relevant
Clinical Trials Analysis, Monitoring, and Presentation
BioStatistics
Recommender Systems: Evaluation and Metrics
Power and Sample Size for Multilevel and Longitudinal...
Introduction to Statistics
Quantitative Research Methods
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2024 OpenCourser