Stata Training in Kenya — Beginner to Advanced
Stata is one of the most powerful statistical analysis tools for postgraduate researchers, economists, and public health professionals. Our expert-led Stata training programme — delivered in three practical modules — takes you from data entry and basic commands all the way to advanced regression, panel data analysis, and econometric testing.
Course Details
What is Stata & Why Should You Learn It?
Stata is a multi-purpose statistical software package used to explore, summarize, and analyze datasets. It is widely adopted in social science research, economics, public health, and postgraduate academic research across Kenya and globally.
Stata offers a gradual learning curve compared to other statistical tools — it combines point-and-click menus with a powerful command-line interface, making it accessible to beginners while remaining highly capable for advanced researchers running complex econometric models.
For Masters and PhD students in Kenya, Stata is one of the most commonly required tools for panel data analysis, regression modelling, and hypothesis testing — particularly in economics, education, business, and public health dissertations.
| Feature | SPSS | Stata ✓ | R | SAS |
|---|---|---|---|---|
| Learning Curve | Gradual | Gradual | Steep | Steep |
| Interface | Click & Menu | Both | Programming | Programming |
| Panel Data | Limited | Excellent | Good | Good |
| Data Analysis | Very Strong | Very Strong | Very Strong | Very Strong |
| Graphics | Good | Very Good | Excellent | Good |
| Cost | Expensive | Affordable | Free | Expensive |
The Three-Module Learning Path
Each module builds on the last — giving you a complete, structured progression from your first Stata command to advanced regression models used in PhD-level research.
Introduction to Stata
Learn the Stata environment, basic commands, data entry, importing from Excel, descriptive statistics, graphs, and simple regression. No prior experience required.
Intermediate Stata
Panel data analysis, diagnostic testing (normality, multicollinearity, heteroscedasticity, autocorrelation), Hausman tests, and fixed and random effects regression.
Advanced Stata
Advanced regression — pooled OLS, FGLS, binary and multinomial logistic regression, probit models, Tobit regression, and other econometric techniques for complex research.
Detailed Module Content
Every topic below is covered hands-on in a live session, using real research datasets. Each module is Ksh 5,000 and runs for 5 hours.
Introduction to Basics of Stata
Data management · Descriptive statistics · Regression & correlation · Data transformation
Basic Stata Features & Data Management
Descriptive Statistics
Regression & Correlation
Transformation of Data
Intermediate Stata
Panel data analysis · Diagnostic tests · Hausman tests · Panel regression
Diagnostic Tests for Panel Data
Hausman Tests
Panel Regression & Correlation
Advanced Stata
Advanced regression · Logistic models · Probit · Tobit · FGLS regression
Advanced Regression Analysis — Part 1
Advanced Regression Analysis — Part 2
Key Stata Features You Will Master
Stata is a complete research analysis environment. Here are the core capabilities covered across our three training modules.
Data Management
Import from Excel and CSV, manage datasets, rename variables, recode and transform data, merge and append datasets, and create log files to track all your work.
Descriptive Statistics
Frequency tables, crosstabulations, means, standard deviations, ranges, variance, and subgroup analysis — all essential for your Chapter Four results section.
Correlation Analysis
Pearson and Spearman correlation, correlation matrices, and interpretation of coefficient direction and strength for your research findings.
Regression Analysis
OLS regression, panel data regression (fixed and random effects), logistic, probit, and Tobit models — covering hypothesis testing and coefficient interpretation.
Diagnostic Testing
All Classical Linear Regression Model (CLRM) assumptions — normality, multicollinearity, heteroscedasticity, autocorrelation, and stationarity — tested and resolved.
Data Visualization
Scatterplots, histograms, bar charts, and categorical graphs — Stata produces publication-quality visualizations for presentations, theses, and journal submissions.
Common Stata Commands You Will Learn
Our training is entirely practical. You will work with real commands on real datasets — not just theory. Here is a taste of what you will learn to write and interpret.
* Set working directory
cd "C:\mydata"
* Open log file
log using mylog.log
* Import from Excel
import excel "data.xlsx", sheet("Sheet1") firstrow clear
* Describe dataset
describe
summarize
* Rename variable
rename var1 income
* Label variable
label variable income "Monthly Income (KES)"
* Correlation matrix
pwcorr y x1 x2 x3, star(0.05)
* OLS regression
regress y x1 x2 x3, robust
* Test for multicollinearity
vif
* Test for heteroscedasticity
hettest
* Panel data setup
xtset id year
* Fixed effects regression
xtreg y x1 x2 x3, fe
* Random effects regression
xtreg y x1 x2 x3, re
* Frequency table
tab gender
* Crosstabulation
tab gender major, column row
* Descriptive stats by group
tabstat age income score, s(mean sd min max) by(gender)
* Normality test
swilk income
* Histogram with normal curve
histogram income, normal frequency
* Scatterplot with fitted line
twoway scatter y x || lfit y x
* Hausman test (FE vs RE)
hausman fe re
* Binary logistic regression
logit y x1 x2 x3
margins, dydx(*)
* Probit regression
probit y x1 x2 x3
* Tobit regression
tobit y x1 x2 x3, ll(0)
* FGLS regression
xtgls y x1 x2 x3, panels(heteroskedastic)
* Save results
estimates store model1
Who Should Attend Stata Training?
Our Stata training is designed for anyone who works with quantitative data — from first-time students to experienced researchers who need to expand their analytical toolkit.
Masters Students
Required to perform data analysis for Chapters 4 and 5 of your thesis? Our Module 1 and 2 will equip you with everything you need for descriptive statistics, correlation, and regression.
PhD Researchers
Working with panel data, running econometric models, or dealing with complex diagnostic issues? Module 2 and 3 cover the advanced techniques required at doctoral level.
Economists & Finance Researchers
Stata is the industry standard for panel data and econometrics. Learn fixed/random effects, FGLS, and time-series analysis tailored to economics and finance dissertations.
Public Health & Social Science Researchers
Learn logistic regression, probit models, and cross-sectional analysis techniques widely used in public health, sociology, and education research.
Professionals & Analysts
Need Stata skills for workplace data analysis, government reporting, or research consultancy? Our practical, output-focused training gets you productive fast.
SPSS or Excel Users Switching to Stata
Stata 16+ can import SPSS and SAS data directly. We cover how to transition your existing datasets and workflow into Stata seamlessly — including the command-line approach.
Frequently Asked Questions
Common questions about our Stata training programme before you book.
Book Your Stata Training Session
Fill in our booking form or reach out directly. Our team is available Monday to Saturday to confirm your slot and answer any questions about the training content.
Have Questions? Contact Us Directly
We are happy to help you decide which module to start with or answer any questions about the training programme.
