Format: Live instructor-led online training via Zoom / Microsoft Teams

Impact Evaluation and Data Analysis of Programmes Course

Introduction

The Impact Evaluation and Data Analysis of Programmes Course is designed to equip professionals with advanced skills in evaluating development programmes, projects, and policies using robust quantitative and qualitative data analysis techniques. In today’s results-driven environment, organizations require evidence-based decision-making to measure programme effectiveness, efficiency, sustainability, and impact. This course provides practical knowledge in impact evaluation methodologies, statistical analysis, and data-driven reporting, ensuring participants can generate credible and actionable insights.

With increasing demand for accountability and transparency in development programmes, NGOs, government agencies, and international organizations are adopting advanced monitoring and evaluation (M&E) systems. This training focuses on impact evaluation designs such as randomized controlled trials (RCTs), quasi-experimental methods, baseline and endline surveys, and counterfactual analysis. Participants will gain hands-on experience in data collection, management, and analysis using tools such as Excel, SPSS, R, Stata, and other data analytics platforms.

The course emphasizes practical application through real-world case studies in sectors such as health, education, agriculture, humanitarian response, and economic development. Participants will learn how to design evaluation frameworks, develop indicators, analyze datasets, and communicate findings effectively to stakeholders. The integration of statistical techniques with programme evaluation ensures participants can assess causal relationships and measure the true impact of interventions.

By the end of the training, participants will be able to design and implement impact evaluations, manage complex datasets, apply statistical analysis methods, and produce high-quality evaluation reports. This course enhances professional capacity in monitoring and evaluation, making it ideal for those seeking to strengthen programme performance, policy analysis, and organizational learning.

Course Objectives

1. Understand the principles and frameworks of impact evaluation.
2. Design evaluation studies using experimental and quasi-experimental methods.
3. Develop indicators and logical frameworks for programme evaluation.
4. Apply quantitative and qualitative data analysis techniques.
5. Conduct baseline, midline, and endline surveys.
6. Use statistical software (SPSS, R, Stata, Excel, python) for data analysis.
7. Interpret evaluation results and draw actionable conclusions.
8. Assess programme effectiveness, efficiency, and sustainability.
9. Strengthen skills in report writing and data visualization.
10. Apply ethical considerations in data collection and evaluation.

Organization Benefits

1. Improved evidence-based decision-making and programme design.
2. Enhanced accountability and transparency in project implementation.
3. Stronger monitoring and evaluation systems.
4. Better resource allocation through data-driven insights.
5. Increased programme effectiveness and measurable impact.
6. Improved reporting to donors and stakeholders.
7. Strengthened capacity for data analysis and evaluation.
8. Identification of programme strengths, weaknesses, and opportunities.
9. Enhanced organizational learning and continuous improvement.
10. Competitive advantage in securing funding and partnerships.

Target Participants

• Monitoring and evaluation (M&E) specialists.
• Data analysts and statisticians.
• Programme and project managers.
• Researchers and policy analysts.
• NGO and development practitioners.
• Government officials and planners.
• Donor agency staff and consultants.
• Academics and graduate students in development studies.

Course Outline

Module 1: Introduction to Impact Evaluation

1. Concepts and importance of impact evaluation.
2. Difference between monitoring, evaluation, and impact assessment.
3. Theory of change and results frameworks.
4. Evaluation questions and objectives.
5. Overview of evaluation designs.
6. Case study: Evaluating a rural development programme.

Module 2: Evaluation Design and Methodologies

1. Experimental designs (Randomized Controlled Trials – RCTs).
2. Quasi-experimental methods (DID, PSM, regression discontinuity).
3. Sampling techniques and sample size determination.
4. Internal and external validity.
5. Counterfactual analysis.
6. Case study: Impact evaluation of a health intervention.

Module 3: Data Collection Methods

1. Designing surveys and questionnaires.
2. Qualitative data collection (FGDs, KIIs, observations).
3. Digital data collection tools (ODK, KoboToolbox).
4. Data quality assurance and validation.
5. Ethical considerations in data collection.
6. Case study: Baseline survey for education programmes.

Module 4: Data Management and Cleaning

1. Data entry, coding, and database design.
2. Data cleaning and validation techniques.
3. Handling missing data and outliers.
4. Data transformation and recoding.
5. Data documentation and metadata.
6. Case study: Cleaning household survey data.

Module 5: Descriptive Data Analysis

1. Descriptive statistics (mean, median, mode).
2. Frequency distributions and cross-tabulations.
3. Data visualization (charts, graphs, dashboards).
4. Exploratory data analysis (EDA).
5. Using Excel and SPSS for descriptive analysis.
6. Case study: Analysis of agricultural productivity data.

Module 6: Inferential Statistics

1. Hypothesis testing and confidence intervals.
2. Correlation and regression analysis.
3. T-tests and ANOVA.
4. Non-parametric tests.
5. Interpreting statistical results.
6. Case study: Income impact analysis of microfinance programmes.

Module 7: Advanced Impact Evaluation Techniques

1. Difference-in-Differences (DID) analysis.
2. Propensity Score Matching (PSM).
3. Instrumental variables approach.
4. Regression discontinuity design.
5. Sensitivity analysis.
6. Case study: Evaluating social protection programmes.

Module 8: Qualitative Data Analysis

1. Coding and thematic analysis.
2. Content and narrative analysis.
3. Using qualitative software (NVivo, Atlas.ti).
4. Triangulation of qualitative and quantitative data.
5. Reporting qualitative findings.
6. Case study: Gender empowerment programme evaluation.

Module 9: Data Visualization and Reporting

1. Designing effective data visualizations.
2. Dashboard development and storytelling.
3. Writing evaluation reports.
4. Communicating findings to stakeholders.
5. Policy briefs and presentations.
6. Case study: Donor reporting for development programmes.

Module 10: Monitoring and Evaluation Systems

1. Designing M&E frameworks and indicators.
2. Performance monitoring tools.
3. Logical framework (logframe) development.
4. Results-based management (RBM).
5. Integration of M&E systems in organizations.
6. Case study: M&E system for a humanitarian project.

Module 11: Ethics and Quality Assurance in Evaluation

1. Ethical standards in evaluation research.
2. Data privacy and protection.
3. Bias and validity in evaluation studies.
4. Quality assurance frameworks.
5. Risk management in evaluation.
6. Case study: Ethical challenges in field data collection.

Module 12: Final Project and Practical Application

1. Designing a complete impact evaluation plan.
2. Data collection and analysis project.
3. Interpretation of findings and recommendations.
4. Report writing and presentation.
5. Peer review and feedback.
6. Final case study: End-to-end programme impact evaluation.

General Information

1. Customized Training: All our courses can be tailored to meet the specific needs of participants.
2. Language Proficiency: Participants should have a good command of the English language.
3. Comprehensive Learning: Our training includes well-structured presentations, practical exercises, web-based tutorials, and collaborative group work. Our facilitators are seasoned experts with over a decade of experience.
4. Certification: Upon successful completion of training, participants will receive a certificate from Foscore Development Center (FDC-K).
5. Training Locations: Training sessions are conducted at Foscore Development Center (FDC-K) centers. We also offer options for in-house and online training, customized to the client's schedule.
6. Flexible Duration: Course durations are adaptable, and content can be adjusted to fit the required number of days.
7. Onsite Training Inclusions: The course fee for onsite training covers facilitation, training materials, two coffee breaks, a buffet lunch, and a Certificate of Successful Completion. Participants are responsible for their travel expenses, airport transfers, visa applications, dinners, health/accident insurance, and personal expenses.
8. Additional Services: Accommodation, pickup services, freight booking, and visa processing arrangements are available upon request at discounted rates.
9. Equipment: Tablets and laptops can be provided to participants at an additional cost.
10. Post-Training Support: We offer one year of free consultation and coaching after the course.
11. Group Discounts: Register as a group of more than two and enjoy a discount ranging from 10% to 50%.
12. Payment Terms: Payment should be made before the commencement of the training or as mutually agreed upon, to the Foscore Development Center account. This ensures better preparation for your training.
13. Contact Us: For any inquiries, please reach out to us at training@fdc-k.org or call us at +254712260031.
14. Website: Visit our website at www.fdc-k.org for more information.