Advanced Tools for Quantitative and Qualitative M&E Data Analysis Training Course

Introduction

Monitoring and Evaluation (M&E) professionals are increasingly required to master both quantitative and qualitative data analysis to provide credible evidence for decision-making and policy development. The Advanced Tools for Quantitative and Qualitative M&E Data Analysis Training Course is designed to strengthen participants’ capacity to handle complex datasets, perform statistical and thematic analyses, and interpret results to guide strategic program improvement.

This course delves into advanced analytical techniques that help participants move beyond basic descriptive analysis to more robust inferential, predictive, and mixed-method approaches. It emphasizes the integration of data science tools, modern visualization software, and qualitative coding techniques to ensure that findings are comprehensive, accurate, and actionable.

Participants will gain hands-on experience using leading analytical software such as SPSS, Stata, R, NVivo, ATLAS.ti, and Excel, applying them to real M&E datasets. They will learn how to combine numerical and narrative evidence to uncover trends, assess program impact, and explain contextual variations that shape development outcomes.

The course also focuses on strengthening participants’ data interpretation, storytelling, and reporting capabilities transforming complex analysis results into strategic insights for managers, policymakers, and stakeholders. Learners will explore how data analytics can improve accountability, transparency, and learning within organizations.

Special sessions address emerging issues such as AI-assisted data analysis, data quality assurance, triangulation techniques, and the ethical use of data. These modules ensure participants stay at the forefront of evidence-based evaluation in an era of digital transformation and big data.

By the end of the training, participants will have the competence to apply advanced quantitative and qualitative data analysis tools in designing, implementing, and evaluating complex M&E frameworks leading to stronger evidence generation and more informed decision-making.

Who Should Attend

• Monitoring and Evaluation specialists and officers
• Data analysts and statisticians involved in program evaluation
• Research officers and consultants in development and social sectors
• Project and program managers seeking data-driven performance insights
• Policy analysts and decision-makers relying on evaluation data
• Academics and postgraduate students in M&E and development fields
• NGOs, donor agencies, and government program officers
• Professionals using statistical and qualitative software in their work
• Impact assessment and learning officers in development organizations
• Anyone interested in mastering mixed-methods data analysis for M&E

Course Objectives

By the end of the course, participants will be able to:

• Develop advanced skills in quantitative and qualitative data analysis for M&E
• Apply statistical and thematic techniques for robust program evaluation
• Use software tools such as SPSS, Stata, R, NVivo, and ATLAS.ti for data analysis
• Integrate mixed-method approaches to strengthen evidence credibility
• Enhance data quality, validation, and reliability during analysis
• Translate analytical findings into clear, actionable insights for decision-making
• Visualize and communicate data effectively using modern visualization tools
• Conduct regression, factor, and impact analyses for complex projects
• Manage, clean, and triangulate multi-source data for comprehensive evaluations
• Apply AI-assisted and emerging analytical methods for M&E innovation

Comprehensive Course Outline

Module 1: Foundations of Advanced M&E Data Analysis

• Overview of quantitative and qualitative approaches in M&E
• Principles of data triangulation and evidence integration
• Identifying key variables and indicators for analysis
• Ethics and data integrity in M&E research

Module 2: Quantitative Data Management and Preparation

• Data entry, cleaning, and coding techniques
• Handling missing values, outliers, and biases
• Structuring datasets for statistical analysis
• Quality assurance and verification procedures

Module 3: Advanced Statistical Analysis Techniques

• Descriptive, inferential, and multivariate statistics
• Regression, correlation, and factor analysis
• Hypothesis testing and sampling strategies
• Interpretation of statistical results for program learning

Module 4: Working with Statistical Software Tools

• Hands-on training in SPSS, Stata, and R
• Automation and scripting for advanced analysis
• Importing and merging multiple datasets
• Data visualization using R and Power BI

Module 5: Qualitative Data Collection and Management

• Designing qualitative data frameworks for M&E
• Transcription, coding, and categorization of text data
• Managing interviews, focus groups, and field notes
• Ethical considerations in qualitative data use

Module 6: Qualitative Data Analysis Techniques

• Thematic, content, and discourse analysis
• Grounded theory and narrative approaches
• Coding and memoing using NVivo and ATLAS.ti
• Triangulation between qualitative and quantitative findings

Module 7: Integrating Mixed-Methods Analysis

• Designing mixed-methods M&E frameworks
• Convergent, explanatory, and exploratory designs
• Integrating survey and case study data
• Synthesizing quantitative and qualitative evidence

Module 8: Data Visualization and Reporting

• Turning complex data into meaningful visuals
• Creating dashboards using Excel and Power BI
• Storytelling with data and evidence presentation
• Writing analytical reports for different audiences

Module 9: Emerging Tools and Technologies in M&E Analysis

• AI and machine learning in data analysis
• Cloud-based M&E data platforms
• Real-time analytics for adaptive programming
• Open-source innovations for development analytics

Module 10: Application and Case Studies

• Practical analysis using real-world datasets
• Evaluation of complex multi-sectoral projects
• Case examples from health, education, and governance sectors
• Peer review and group presentations of analytical findings

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808

Training Venue 

The training will be held at our Upskill Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Upskill certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808 

Terms of Payment

Unless otherwise agreed between the two parties’ payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.