Upon successful completion of this course participants should be able to:

• Discuss the relevance of reliable data collection process in Research
• Design appropriate research instruments
• Use relevant computer packages for data management and extrapolation
• Link research results to successful policy implementation
• Introduce the concepts of monitoring and evaluation and the value of implanting it in programs/projects
• Focus participant’s attention on monitoring and evaluation study designs
• M&E Data Management and Analysis
• To introduce participants to GIS software, data capture methods, analysis, data importation and mapping indicators using GIS Techniques)
• Get hands on skills on SPSS, STATA & NVIVO
• Conduct Project Evaluations
• Engage in Project Operational Research
• Embrace use of data in informed decision making

Main Modules

• Fundamental concepts and tools for monitoring and evaluating programs Advanced Microsoft Excel.
• Observational data, quasi-experiments and correlation studies
• Social experiments, natural experiments and Randomized control trials Qualitative evaluation designs
• Conceptual issues in M&E data Data types and sources Planning data Collection
• Selecting study elements (Sampling) ICT tools for Data processing Comparison of Data analysis packages Basic data quality checks
• Basic exploratory data analysis procedures
• Introduction to Quantitative analysis (Descriptive Summaries, Data Tabulation methods) o Graphing qualitative data Graphing Quantitative data
• Performing common inferential statistical test (t-test, correlation, Chi Square, Analysis of variance (ANOVA)
• Regression Analysis and Econometrics
• Introduction to Geographic Information System (GIS)
• Introduction to GIS Software (Quantum GIS)
• Mobile GPS Field Work
• Mapping M&E Indicators with Quantum GIS
• Participatory Mapping and collective intelligence (Google Maps, Google Earth)
• Application and use of STATA
• Application/Use of Nvivo
• Importing and Coding Documents Importing and coding other items Classifying and Categorizing Data Grouping your data: collections and links Models and relationships
• Reporting and presenting your findings.

Course Booking

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