Statistical Data Analysis with Stata Training Course

This five-day, hands-on course builds the skill to analyse data in Stata, from preparing a dataset to interpreting and reporting results. It covers the Stata environment and data management, descriptive statistics and exploration, the main inferential tests, regression analysis, and reproducible workflows using do-files. Participants leave able to take a dataset from raw to results in Stata and to interpret the output with confidence.

Stata is the tool of choice for a great deal of serious research and analysis, especially in economics, public health, the social sciences and impact evaluation. It combines an approachable interface with a powerful command language, and its do-files make analysis reproducible, which is increasingly essential for credible research. Where rigorous quantitative analysis is needed, Stata is very often where it is done.

This course builds genuine competence in it. It covers the Stata environment and how to manage and prepare data, descriptive statistics and exploration, the main inferential tests, regression analysis for modelling and prediction, and the use of do-files to make analysis reproducible. It teaches both the menus and the commands, so participants leave able to work efficiently and to read and write Stata code. Participants leave able to take a dataset from raw to results in Stata, choose and run the right analysis, interpret the output correctly, and produce reproducible work. The course is hands-on, with every participant working in Stata throughout.

• Navigate the Stata environment and work efficiently with commands, datasets and output
• Write, save and run do-files to create reproducible analytical workflows
• Import data from common sources and structure it appropriately for analysis in Stata
• Clean, inspect and validate data, and identify common data quality issues
• Generate, replace, label, recode and transform variables for analysis
• Merge, append and reshape datasets for different analytical purposes
• Produce descriptive statistics, tabulations and exploratory summaries
• Select and run appropriate inferential techniques for common analytical questions
• Conduct and interpret t-tests, ANOVA, chi-square tests and correlation analyses
• Build and interpret simple linear, multiple linear and introductory logistic regression models
• Understand core model diagnostics and post-estimation considerations at an applied level
• Present results clearly and maintain an auditable, reproducible record of analytical work

This course is designed for professionals who need to manage, analyse and report quantitative data using Stata, including:

• Researchers, research assistants and quantitative field staff
• Monitoring and evaluation officers, analysts and managers
• Economists, policy analysts and planning staff
• Public health, epidemiology and health systems professionals
• Government, NGO and development sector analysts
• Data officers, statistics personnel and information management staff
• Consultants and professionals who need a reproducible statistical workflow
• Anyone who wants to move from spreadsheet-based analysis to a more rigorous statistical environment

The course is delivered in a hands-on computer lab format. Each technique is demonstrated, then practised immediately on real and realistic datasets, using both menus and commands. Reproducibility through do-files runs throughout, and a daily practical session takes an analysis from data to findings.
•Live demonstration and guided practice in Stata
•Hands-on analysis of real and realistic datasets
•Writing and using do-files for reproducible analysis
•Step by step interpretation of output
•A daily practical session and a final analysis project

Organisations whose teams complete this course can expect:

• More efficient and reproducible handling of quantitative data and analysis
• Stronger internal capability for research, evaluation, public health and policy analysis
• Better quality evidence for reporting, programme improvement and decision-making
• Reduced reliance on external consultants for routine statistical analysis
• More transparent and auditable analytical workflows
• Improved consistency in how findings are generated, documented and updated
• Better use of existing datasets through stronger in-house analytical capacity
• A more technically capable team able to produce credible quantitative outputs

Participants completing this course will gain:

• Practical confidence in using Stata as a professional analytical tool
• The ability to build and maintain reproducible do-file based workflows
• Stronger discipline in data management and statistical analysis
• Better judgement in selecting the right method for the question and the data
• Improved confidence in interpreting results and explaining them clearly to others
• Greater independence in handling research, M&E and policy datasets
• A valuable quantitative skill widely recognised across research, economics, evaluation and public health
• A foundation for progressing into more advanced Stata analysis and econometric work

At Strategic Revenue Africa, our certification goes beyond proof of attendance—it represents practical competence and measurable capability. Upon successful completion of our training programs, participants are awarded a Certificate of Completion from Strategic Revenue Africa, recognizing their ability to apply acquired knowledge in real-world settings. As an organization focused on architecting sustainable revenue and strengthening organizational performance, our certifications signal that participants are equipped with skills that drive results, not just theory.

Basic computer literacy is required. No prior Stata experience is necessary, and no advanced background in statistics is assumed. The course is suitable for participants who are new to Stata as well as those who have some exposure to it but want a more structured and reproducible approach to data analysis. A basic familiarity with datasets, spreadsheets or quantitative reporting will be helpful but is not essential. Participants should have access to Stata during the course.