Research Design
Design research grounded in best practices for measuring impact. Covers sampling strategies, randomization methods, power calculations, measurement frameworks, and implementation best practices for RCTs and other research designs.
MEL
Monitoring, Evaluation, and Learning guidance to help organizations build data-driven learning. Includes A/B testing, theory of change development, and practical resources for continuous learning based on right-fit approaches to data and methods.
Research Ethics
Plan for and navigate ethical considerations including informed consent, data privacy, and IRB processes. Provides guidance on ethical compliance, human subjects protection, and institutional review requirements.
Data Quality
Implement validation, cleaning,…
Research Design
Design research grounded in best practices for measuring impact. Covers sampling strategies, randomization methods, power calculations, measurement frameworks, and implementation best practices for RCTs and other research designs.
MEL
Monitoring, Evaluation, and Learning guidance to help organizations build data-driven learning. Includes A/B testing, theory of change development, and practical resources for continuous learning based on right-fit approaches to data and methods.
Research Ethics
Plan for and navigate ethical considerations including informed consent, data privacy, and IRB processes. Provides guidance on ethical compliance, human subjects protection, and institutional review requirements.
Data Quality
Implement validation, cleaning, and management practices to ensure data integrity. Covers quality assurance methods, error detection techniques, and protocols for maintaining reliable datasets.
Data Collection
Master digital and field data collection methods using modern tools and techniques. Provides strategies for designing efficient, reliable data collection systems and managing field operations.
Data Cleaning
Address common data issues including missing values, outliers, and inconsistencies. Offers practical guides, code examples, and systematic approaches for preparing data for analysis.
Software Guides
Learn essential tools for research, data science, and MEL projects. Provides tutorials and best practices for Stata, Python, R, and other software commonly used in research, evaluation, analysis, and software development.