The Complete Guide to Stata

[Updated with new Audio in 2025]

The Complete Guide to Stata

Are you ready to harness the full power of Stata for data analysis? Whether you’re a complete beginner or an experienced analyst looking to sharpen your skills, this course provides a thorough, hands-on introduction to Stata’s most useful features. You’ll learn to manipulate, explore, visualize, and model complex datasets—all while developing “good practice” habits that will help you code efficiently, interpret results correctly, and present your findings with confidence.

This course is split into three main sub-courses to guide your learning:

1. Stata Fundamentals – A step-by-step introduction to the essentials of Stata, from data loading and cleaning to basic descriptive statistics and graphing.

2. Stata Tips and Tricks – Explore 125 short, standalone tips to help you solve common challenges, speed up your workflow, and uncover hidden capabilities within Stata.

3. Advanced Data Visualization – Master a wide variety of visualization techniques, learning how (and when) to use each one effectively.

I'll consistently focus on practical application - rather than diving into lengthy statistical theory - and show you how to implement and interpret commonly used statistical methods with real-world data.

What You’ll Learn

• Getting Started: Install and navigate Stata with ease.

• Data Exploration and Management: Load, view, clean, and manipulate datasets for proper analysis.

• Basic and Advanced Visualizations: Create histograms, box plots, scatter plots, violin plots, spike plots, line charts, and more—while understanding the pros and cons of each.

• Statistical Analysis:

  • Correlation and ANOVA

  • Regression (including diagnostics and model building)

  • Hypothesis Testing

  • Binary Outcome Models (Logit/Probit)

  • Fractional Response Models

  • Categorical Choice Models (Ordered Logit/Multinomial Logit)

  • Simulation Techniques

  • Count Data Models (Poisson/Negative Binomial)

  • Survival Data Analysis (Parametric, Cox-Proportional Hazard, Parametric Survival Regression)

  • Panel Data Analysis (including Lags, Leads, Fixed/Random Effects, Hausman Tests)

  • Difference-in-Differences Analysis

  • Instrumental Variable Regression (Endogenous Variables, Sample Selection, Non-Linear Endogenous Models)

• Epidemiological Tables: Cohort studies, case-control studies, and matched case-control studies.

• Power Analysis: Determine sample size, power size, and effect size.

• Matrix Operations: Operators, functions, and subscripting.

You’ll also get 125 “Tips and Tricks” to help you become a Stata power user, covering topics like data management, graphing, statistics, and programming. Each standalone tip takes just a couple of minutes to learn and immediately apply.

Finally, the Advanced Data Visualization portion of the course will guide you through a diverse range of graphing techniques—from histograms and rootograms to bubble plots and mosaic plots—giving you the skills to present data in clear, compelling ways.

Prerequisites and Target Audience

• Prerequisites: No prior experience with Stata is required. Familiarity with basic quantitative concepts is helpful but not mandatory.

• Who Should Enroll: Anyone who wants to enhance their data analytics skill set with professional Stata techniques, including students, researchers, data scientists, and analysts in business, academia, and the public sector.

Suggested Learning Paths

Depending on your goals, you may wish to focus on certain sections:

• Basic Stata Fundamentals: Sections 2, 3, 4, 5, 6, 7, 8

• Advanced Stata Concepts: Sections 8, 9, 10, 11, 12, 13, 14, 15, 16, 17

• Quick Tips and Tricks: Sections 18, 19, 20, 21

• Data Visualization: Sections 5, 21, 22, 23, 24, 25, 26

• Data Management: Sections 3, 4, 18

Take this course to experience Stata at its finest; learn the coding, analytic, and visualization skills you need to excel in modern data analysis, and gain the confidence to tackle real-life projects with competence and clarity.