This training course on project M&E and data analysis focuses on the principles and practices for results-based monitoring and evaluation throughout the project life cycle, as well as data management and analysis. This means that the participants for this course will not only gain skills in establishing and implementing results-based monitoring and evaluation systems but will also get equipped with abilities to execute M&E functions through the latest data management, analysis, and reporting practices.

Training Locations and Dates

Target Participants

This course is designed for researchers, project staff, development practitioners, managers/decision makers and independent consultants who are responsible for project, programmes or policies monitoring, learning, and evaluation.

What you will learn

By the end of the course the learner should be able to:

• Develop project results levels
• Design a project using logical framework
• Develop indicators and targets for each result level
• Track performance indicators over the life of the project
• Evaluation a project against the set results
• Develop and implement M&E systems
• Develop a comprehensive monitoring and evaluation plan
• Use of data analysis software (Stata/SPSS/Excel/R)
• Collect data using mobile data collection tools
• Carryout impact evaluation

Course Duration

5 days

Course Outline

Introduction to Project Management

• Introduction to project management
• Project cycle management
• Triple constraints in project management
• M&E in project management

Introduction to M&E

• Definition of monitoring and evaluation
• Why monitoring and evaluation is important
• Key principles and concepts in M&E
• Monitoring and evaluation processes

Results-Based Management

• Introduction to results-based management approach
• Steps in results-based management
• Application of results-based management in project design
• Understanding the results chain approach

Project Analysis

• Problem analysis
• Objectives analysis
• Strategy analysis

Project Logic Design

• Introduction to problem analysis
• Understanding M&E causal pathway
• Developing the project results levels: goal, outcomes and output
• Formulating activities

Project Indicators

• Introduction to project indicator
• Indicator development
• Predefined indictors
• Linking indicators to results in programs
• Indicator matrix
• Program indicator performance tracking

Completing the M&E Tools

• Completing the logical framework
• Developing a theory of change
• Completing the performance measurement framework

Project Monitoring

• Introduction to programs monitoring
• Types of monitoring
• Monitoring strategies
• Tools for monitoring and performance measurement

M&E Reporting

• Introduction to reporting
• Key elements in progress reporting
• Reporting schedules

M&E Plan

• Introduction to M&E system and M&E Plan
• Components of the M&E Plan
• Developing the M&E Plan
• Implementing the M&E plan

Baseline Studies in Results based M&E

• Importance of baseline studies
• Process of conducting baseline studies
• Baseline study vs evaluation

Project Evaluations

• Introduction to project evaluation
• Types of evaluations
• Process of conducting evaluation
• Project evaluation criteria
• Developing evaluation questions
• Developing evaluation matrix
• Evaluation reporting

Overview of Impact Evaluation

• Introduction to impact evaluation
• Project attribution for outcome of interest
• Impact evaluation designs

Learning in M&E

• Introduction to learning
• Documentation of lessons learned and best practices
• Use of learning to improve and strengthen projects
• M&E Results dissemination

Gender Mainstreaming in M&E

• Key gender concepts and definitions
• Overview of gender mainstreaming in project management
• Engendering the logical framework
• Development of gender responsive data collection methods and tools

M&E Data Collection Methods and Tools

• Sources of M&E data –primary and secondary
• Qualitative data collection methods
• Quantitative data collection methods
• Participatory data collection methods
• Introduction to data triangulation

Mobile Data Collection

• Introduction to mobile data collection
• Setting up MDC
• Setting up the server
• Design of data collection forms

Introduction to Data Analysis

• Introduction statistics and data analysis
• Understanding descriptive vs inferential statistics
• Understanding variables
• Introduction to data types

Statistical Data Management

• Data cleaning and management

Exploring Data

• Descriptive analysis
• Frequencies
• Basic univariate analysis
• Cross tabulations
• Basic univariate analysis
• Cross tabulations

Comparison Tests

• Understanding parametric vs non-parametric tests
• Choosing a test – decision tree
• Parametric data- T test, ANOVA
• Non-parametric data
• Proportions

Tests of Association

• Introduction to correlation analysis
• Parametric data – Pearson correlation
• Nonparametric data – Spearman rank correlation

Regression Analysis

• Introduction to regression analysis
• Regression diagnostics – measurement error, multicollinearity, heteroskedasticity, endogeneity, non-normality
• Parametric data – linear regression analysis (simple and multiple regression)
• Non-parametric data – non parametric regression
• Categorical dependent variables – logit and probit regression models

 Data Visualization

• Pivot tables
• Graphs and charts
• Dashboards