Because of COVID-19, many providers are cancelling or postponing in-person programs or providing online participation options.
We are happy to help you find a suitable online alternative.
Who should attend
Senior managers and all professionals who might have undertaken the basic Monitoring & Evaluation training and need to progress to the advanced level.
About the course
In an era of demanding stakeholders’ expectations regarding financial probity, budgetary transparency and the proven impact value of funded work programs, monitoring and evaluation (M&E) remains one of those aspects of organizational management that is extensively discussed but rarely practiced.
This Module entails M&E data processing and setting up of effective M&E systems within organizations
- Develop a system to collect and compile data
- Determine an appropriate method of analyzing, presenting and disseminating information to different stakeholders
- Demonstrate the ability to use information to identify problems and implement changes
- Describe and understand the various stages in an M&E system: planning, data collection, making data usable and using data for decision-making to help organizations reflect on and strengthen their plans
- Recap of module I
- Introduction to surveys
- Developing survey instruments and procedures
- Questionnaire design
- Sampling procedures
- Data gathering
- Impact evaluations
- What is impact?
- Why monitor and/or evaluate impact?
- Various techniques: randomization, difference in difference etc.
- Group discussions
Digital Data gathering (Open Data Kit)
- Survey Authoring
- Designing forms manually: Using XLS Forms
- Hosting survey data and platforms for hosting
- Configuring the server
- Preparing the mobile phone for data collection
- Downloading data
- Working with Spatial data (GPS Coordinates)
Comparison of Data analysis packages Excel, SPSS, STATA, R etc.
- Plenary discussion with participants
- Rationale for choosing software for analysis
- Qualitative vs. quantitative data
Variable selection and analytical needs
Data quality: criteria and cleaning processes in excel/SPSS
Introduction to Excel for Data processing and Analysis
- Data Auditing and Validation using Excel
- Variable measures: categorical vs. interval
- Measures of central tendency and association
- Data visualization in excel: graphs, charts and tables
- Overview of SPSS
- Data Management and Graphics with SPSS
Running frequencies in SPSS
- Tests of significance: comparing groups/areas
- Tests of Association (Cross-tabs, Chi-Squared, Tau, Eta, Phi & Cramer’s V) Tests of
Difference (T Test, Chi-Squared)
- Analysis of Variance (ANOVA)
- Correlation Analysis (Pearson, Spearman)
- Regression Analysis
- Interpreting data: statistical inference
- Data for decision making
- Understanding stakeholder needs
- Knowledge management