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.