Course Objectives
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
• To introduce the concepts of monitoring and evaluation and the value of implanting it in programs/projects
• To 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
• Conduct project Evaluations
• Engage in project operational Research
• Embrace use of data in informed decision making
Course Contents
•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
Who Should Attend?
The course is recommended for the following;
• Departmental heads
• Data manager
• Research students
• Project or Departmental managers
• Project officers
• Staffs involved in making informed decision
• Anyone involved in development project
• Anyone who aspires to be a good manager
• Researchers & M&E officers.
Fee information:
The tuition fee is US D 980 Exclusive VAT.
How to Register
Kindly apply through the online application form at…
http://www.aspm.co.ke/index.php/online-application1 or drop us mail at info@aspm.co.ke.
check www.aspm.co.ke for more information