Data Management and Analysis using STATA
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, 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.
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.
Way forward After the Training
Participants will develop a work plan through the help of facilitators that stipulates application of skills acquired in
improving their organizations. ASPM will monitor implementation progress after the training.
Training Evaluation:
Participants will undertake a simple assessment before the training to gauge knowledge and skills on data analysis &
management, another assessment will be done after the training in-order to demonstrate knowledge gained through
the training.