Training Course in Data Analysis Using Stata
This intensive 5-day training is designed to equip researchers, analysts, and professionals with practical skills in data management, statistical analysis, and visualization using Stata, one of the most powerful statistical software tools available today.
Course Overview
| Course Title | Training Course in Data Analysis Using Stata |
| Organization | Tech For Development (T4D) |
| Venue | Tech For Development (T4D) Training Center along Tala Road, Runda, Nairobi |
| Target Industries |
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| Target Job Roles |
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| Course Fees (Face-to-Face) | USD 1,100/KES 75,000 (Exclusive of VAT) |
| Course Fees (Virtual) | TBA |
| Training Modes | Virtual and face-to-face training |
| Payment | Payment should be made to the Tech For Development (T4D) bank account on or before the start of the course |
| Accreditation | Tech For Development Certificate of Course Completion |
Introduction
This intensive 5-day training is designed to equip researchers, analysts, and professionals with practical skills in data management, statistical analysis, and visualization using Stata, one of the most powerful statistical software tools available today.
Duration
5 days
What You’ll Learn
During this training, you will learn to:
- Import, clean, manipulate, and transform datasets efficiently
- Explore and summarize your data through descriptive and inferential techniques
- Build and interpret predictive and regression models; analyze panel and time-series data
- Generate compelling, publication-ready outputs through automation and reproducible workflows
Who Should Attend
- Data analysts
- Researchers
- Data scientists
- Business analysts
- Statisticians
- Anyone working with survey data or performing statistical analysis
Training Methodology
- Instructor-led presentations and live demonstrations
- Hands-on practical exercises per module
- Small group discussions and peer learning
- Real-world datasets for practice
- Supplementary materials and templates
Course Objectives
By the end of this course, participants will be able to:
- Navigate Stata’s interface and workflow, including the Command window, Do-files, Variables window, and result navigation to perform quality analyses.
- Import, export, merge, append, and reshape datasets, as well as handle missing values
- Generate summary statistics and descriptive tables; visualize distributions and relationships with customizable graphs like histograms, scatterplots, bar charts, and line plots
- Conduct hypothesis testing using t‑tests (one-sample, independent, paired), ANOVA, and correlation tests
- Build and interpret simple, multiple linear regressions, as well as logistic and ordinal regression models
- Perform econometric analyses on cross-sectional, panel, and time-series datasets to support policy, financial, or research-driven decision-making
Course Modules
Course Modules
Module I: Introduction to Stata & Data Management
- Overview of Stata interface, files, do-files, logs
- Importing/exporting data, browsing, and saving datasets
- Creating and managing variables: labeling, renaming, generating, replacing
- Merging, appending, and reshaping datasets (wide - long)
- Using loops (foreach, forvalues), summary statistics, and egen functions
- Basic graphing (e.g., line plots, scatter plots)
Module II: Exploratory Data Analysis & Graphics
- Summary tables and descriptive statistics
- Data exploration techniques: distributions, outliers, grouping
- Creating and customizing graphs: histograms, bar charts, scatter plots, boxplots
- Exporting visualization outputs for reporting
Module III: Statistical Tests & Measures of Association
- Hypothesis testing: one-sample, independent, paired t-tests, one-way ANOVA
- Nonparametric tests where applicable
- Measures of association: chi-square tests, Pearson, and Spearman correlations
Module IV: Regression Modeling
- Simple and multiple linear regression: assumptions and diagnostics
- Logistic regression (binary outcomes), ordinal regression
- Interpreting regression outputs: coefficients, odds ratios, model fit
Module V: Panel Data & Time Series Analysis
- Handling panel (longitudinal) data: structure and setup
- Fixed effects vs. random effects regression, model selection (e.g., Hausman test)
- Time series basics: data plotting, seasonal differences, autocorrelation, forecasting
Module VI: Econometric & Multivariate Techniques
- Cross-sectional econometrics
- Panel econometric models and advanced estimators
- Application of econometric analysis across data types
Module VII: Workflow Automation & Reporting
- Building reproducible workflows with do-files, loops, and macros
- Exporting results: tables and graphs
- Creating publication-ready outputs tied to transparency and reproducibility
Module VIII: Final Study Project
- Applying all acquired skills to real datasets
- End-to-end workflow: import - clean - analyze - visualize - report
- Presenting findings through polished outputs and interactive visuals
Course Administration
Methodology
This instructor-led training course is delivered using a blended learning approach comprising presentations, guided practical sessions, web-based tutorials, and group work.
Accreditation
Participants will receive a Tech For Development Certificate of Course Completion.
Training Venue
Held at the Tech For Development Training Centre.
Accommodation & Airport Transfer
Arranged upon request.
Email: letstalk@techfordevelopment.com
Phone: (+254) 790 824 179
Tailor-Made
Customised training available.
Payment
Send proof of payment to letstalk@techfordevelopment.com.
