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  1. M&E Library
  2. Topics
  3. Analysis

Analysis

Quantitative and qualitative analysis for M&E programs. Cleaning, coding, descriptive and inferential statistics, thematic analysis, mixed methods, and how to turn collected data into defensible findings.

How Do I Choose?

How to Clean Your Dataset Before Analysis: A Step-by-Step M&E ChecklistA step-by-step checklist for cleaning M&E data after collection. Duplicate detection, outlier identification, skip logic validation, consistency checks, and cleaning log documentation.Qualitative vs Quantitative vs Mixed MethodsQualitative, quantitative, and mixed methods are not a quality ranking. They answer different questions. Here's when to use each, how to combine them, and what integration actually looks like.Surveys vs Interviews vs Focus GroupsThe three most common M&E data collection methods, compared. Surveys tell you how many, interviews tell you why, focus groups tell you what people agree on.

Overviews (2)

Data ManagementThe systematic processes for collecting, storing, securing, and maintaining data quality throughout the data lifecycle to ensure information is accurate, accessible, and usable for decision-making.Triangulation: Using Multiple Sources and Methods to Verify FindingsUsing multiple data sources, methods, or perspectives to cross-verify findings and strengthen the validity of evaluation conclusions.

Quick Reference (9)

BiasCausal InferenceConfounding VariablesContent AnalysisCounterfactualQualitative DataQuantitative DataReliabilityValidity (Internal & External)

Explore Other Topics

EvaluationDesignData Collection & QualityIndicatorsSampling