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The Essential Guide to Stata

Name: The Essential Guide to Stata
Rating: 4.4 (898 reviews)

Accelerate Your Data Analytics Journey with Stata

Created byF. Buscha

Last updated 3/2025

English

What you'll learn

An essential introduction to Stata
Data manipulation in Stata
Data visualisation in Stata
Data analysis in Stata
Regression modelling in Stata
Simulation in Stata
Count data modelling
Categorical data modelling
Survival analysis
Panel Data Analysis
Epidemiology
Instrumental Variables
Power Analysis
Difference-in-Differences

Course content

19 sections • 103 lectures • 14h 17m total length

Introduction1:42

The Stata Interface7:40
Learn about the basic Stata interface. What does each window do and how do you interact with them?
Using Help in Stata5:23
If there's ONE thing you need to know how to use it's how to use help. Once you can use help you can "help" yourself. Learn about the different ways you can find help inside and outside Stata.
Command Syntax4:10
This course is taught via the command syntax (code). Professionals do not use 'point-and-click' to do their work but write all their analysis in code. Learn about the basic Stata syntax and how it works.
.do and .ado Files7:37
Stata is modular and uses something called .do and .ado files to operate. Learn how these are related to Stata code and how you can interact with them.
Log Files5:11
Log files save all your work to a continuously updated log file. This keeps a record of your results and code in case something goes wrong. Learn how to start, end and view a log file in Stata.
Importing Data9:11
Not all data comes in Stata's .dta format. Learn how to import other data types in Stata such as excel spreadsheets.

Viewing Raw Data4:21
Unlikes Excel, Stata does not display the underlying raw data by default. Learn how to access and view the raw data and how to modify it.
Describing and Summarizing7:33
Basic data analysis often requires summary statistics such as means, standard deviation and min/max values. Learn how to get a overview of your data and produce basic summary statistics.
Tabulating and Tables8:42
Not all data is suited for means and standard deviation analysis. Some data requires tabulation or tables. Learn more about how to tabulate data and how to create custom tables in Stata.
Missing Values7:41
Not all data is 100% perfect. Sometimes there are missing values. Learn how Stata handles missing values and how to detect missing data.
Numerical Distributional Analysis6:00
Analysing distributions is an important part of statistical analysis. Learn what commands are available to analyse data distributions numerical in Stata.
Using Weights5:09
Survey data often contains weights that give some observations more or less significance. Learn how to use weights in statistical analysis in Stata.
The New Table Command (Stata 17)9:42

Recoding an Existing Variable4:53
Learn how to recode an existing variables with the recode command. This command is fast and easy to use and allows you to recode numerical values quickly.
Creating New Variables, Replacing Old Variables6:39
A limitation of the recode command is that is has trouble using "if" conditions in data manipulation. Learn how to use the generate and replace command to generate new and replace existing variable using "if" conditions.
Naming and Labelling Variables7:31
New data often requires renaming and labelling to avoid confusion. Learn how to attach labels and rename variables.
Extensions to Generate4:58
If you are looking for a very complex data manipulation then the EGEN command may help. This command offers more complex extensions to generate and allows you to perform complex data manipulations.
Indicator Variables6:58
Indicator/Categorical data is an important data type. Learn how to construct and recode categorical variables.
Keep and Drop Data/Variables2:58
Not all data needs to be retained. Learn how to remove (or keep) selected observations and variables in your data.
Saving Data4:05
Learn how to set the file path and save your data in Stata. Learn how to export your data in other formats.
Converting String Data7:15
String data (data that contains non-numeric characters) can be challenging to deal with. Get a quick introduction on how you can format such data to be useable in data analysis.
Combining Data6:35
Some datasets are split into multiple files. Learn how to merge and append different datasets together to create larger and more complex datasets.
Using Macro's and Loop's Effectively9:33
Advanced users use custom macro's to speed up their workflow. Get an introduction to macro's and learn the basics of looping code over your data.
Accessing Stored Information6:41
Access memory stored results from status estimation commands in Stata. Learn to use R-class and E-class results, the return list, display, and matrix list to automate your do file.
Multiple Loops4:26
Explore multiple loops in Stata, including nested and double loops with two locals (X and I) to generate new variables from the auto data by multiplying variables, demonstrating time saving.
Date Variables8:24
Convert string date information to numeric in Stata using the date function and a flexible Mdy permutation, then format and extract year, month, and day for analysis.
Subscripting over Groups11:03

Graphing in Stata6:29
Learn the basics of graphing in Stata. How to load, save and use graphs and how to change their colour scheme.
Bar Graphs and Dot Charts7:48
Bar charts and dot charts are useful to plot summary statistics over categorical data. Learn how to create bar and dot charts in Stata and what options are most relevant.
Graphing Distributions9:13
Examining distributions visually is an important part of data analysis. Learn how to use histograms and kernel density plots in Stata.
Pie Charts6:20
Pie charts are used to display numerical proportions. Learn how to create and customise pie charts in Stata.
Graphing Custom Functions5:28
Remember that old graphical calculator you used in school that could could create custom functions? Learn how to draw custom functions (e.g. y = 2x^2) in Stata. Learn how this might be useful in a regression scenario.
Contour Plots (and Interaction Effects)9:04
Contour plots allow 3-dimensional visualisation in 2-dimensions via contours. Learn how to use and apply contour plots to Statistical analysis in Stata. These can be useful to visualise complicated interaction effects.
Jitter Data in Scatterplots5:55
Sometimes you need to fake a scatterplot, but retain the original structure. Learn how to use jitter to randomly distribute actual datapoint and why this might be useful
Scatterplots and Lines of Best Fit9:22
Scatterplots allow users to analysis bivariate relationships. Learn how to create scatterplots and overlay lines of best fit to analyse relationships between two variables visually.
Sunflower Plots7:45
Combining Graphs7:35
Learn how to combine multiple graphs into one graph. This can be a powerful way to increase the visual effectiveness of your work. Learn what options you need to know about when combining graphs in Stata.
Changing Graph Sizes4:37
Change Stata graph sizes by adjusting aspect ratio to shape the plot region, or use y size and x size for the full graph, then scale text.
Graphing by Groups6:27
Explore graphing by groups in Stata using the by option to repeat graphs for subgroups, with options like I scale, total, missing, row and column layouts, and compact styling.
Changing Graph Colours7:24
Adding Text to Graphs8:16
Scatterplots with Categories10:44

Association Between Two Categorical Variables6:07
Learn how to test the association (relationship) between two categorical variables in Stata using the tabulate command.
Testing Means6:38
Learn how to perform basic means test across two variables. Is the mean of one variable really different to the mean of another variables? Learn how to perform group mean tests.
Bivariate Correlation6:46
Learn how to perform bivariate correlation (Pearson's correlation) on two more variables.
Analysis of Variance (ANOVA)6:14
A short introduction to basic ANOVA analysis in Stata.

Ordinary Least Squares (OLS) Regression6:39
A brief introduction and example of basic OLS regression in Stata.
Factor Variables in OLS Regression7:30
Learn how to integrate categorical variables into your regression analysis in Stata.
Diagnostic Statistics for OLS Regression16:14
Learn how to perform common diagnostic analysis and tests after a regression in Stata.
Log Dependent Variables and Interaction Effects in OLS Regression8:20
Learn how to run and interpret a log transformed regression. Learn how to use interaction terms in a regression.
Hypothesis Testing in OLS Regression5:16
Learn how to use the test command to perform hypothesis testing after a regression.
Presenting Estimates from OLS Regression7:55
Learn how to output the results from a regression to other programmes such as Word or Excel and how to make your results look professional.
Standardizing Regression Estimates5:24
Graphing Regression Estimates10:20
Oaxaca Decomposition Analysis15:53
Explore Oaxaca decomposition analysis to decompose the wage gap into explained and unexplained components, using education and work experience as controls to assess discrimination and model explanation.
Mixed Models: Random Intercepts and Random Coefficients18:57
Explore linear mixed effects models with random intercepts and random slopes in Stata, using mix to capture unit-specific variation and improve fit beyond ordinary least squares.
Constrained Linear Regression7:37

Binary Choice Models (Logit/Probit Regression)7:27
When a dependent variable is binary it requires a logit/probit regression model for analysis. Learn how to apply such models in Stata.
Diagnostics and Interpretation of Logit and Probit Regression10:33
Learn basic diagnostic tools after a login/probit regression model including goodness-of-fit statistics.
Ordered and Multinomial Choice Models12:52
Ranked or unranked categorical dependent variables require more complex non-linear models. Learn the basics of the ordered logit and multinomial legit regression models in Stata.

Random Numbers6:43
Learn about simulation and how to create basic random numbers in Stata.
Data Generating Process6:17
Learn how we can use random variables to create fake data with known properties.
Simulating a Violation of Statistical Assumptions5:52
Learn how we can test the assumptions of a regression estimator with fake data that has properties that do not match the requirements of the estimator. What happens when our data misbehaves?
Monte Carlo Simulation5:22
Learn about Monte Carlo Simulation and how professionals test the statistical properties of estimation procedures.

Requirements

There are no requirements

Description

[Updated with new Audio in 2025]

Are you ready to unlock the power of Stata for data analytics? Whether you’re new to the platform or looking to build on existing skills, this course provides a comprehensive introduction to Stata and its many capabilities in modern data analysis. You’ll learn how to manipulate, explore, visualize, and model complex datasets, all while establishing “good practice” habits for efficient coding, thorough interpretation of output, and clear presentation of results.

From the very first sessions, I emphasize practical application rather than complex statistical theory. By the end of the course, you’ll be confident in your ability to work with real-life datasets in Stata, selecting and applying the right methods for your analyses and interpreting results accurately.

What You’ll Learn:

Foundations of Stata: Installation, navigation, data loading, and basic housekeeping.
Data Management: Cleaning, transforming, and restructuring data to prepare for analysis.
Data Exploration and Visualization: Summaries, descriptive statistics, and creating clear graphs and charts.
Statistical Techniques:
- Correlation and ANOVA
- Regression (OLS, model diagnostics, and model building)
- Hypothesis Testing
- Binary Outcome Models (Logit and Probit)
- Fractional Response Models
- Categorical Choice Models (Ordered Logit, Multinomial Logit)
- Simulation Techniques (Random Numbers, Simulation)
- Count Data Models (Poisson, Negative Binomial)
- Survival Analysis (Parametric, Cox Proportional Hazard, Parametric Survival Regression)
- Panel Data Analysis (Long Form Data, Lags, Leads, Fixed/Random Effects, Hausman Test)
- Difference-in-Differences
- Instrumental Variables (Endogenous Variables, Sample Selection, Non-Linear Endogenous Models)
Epidemiological Tables: Cohort studies, case-control studies, and matched case-control studies.
Power Analysis: Determining sample size, power size, and effect size.
Matrix Operations: Operators, functions, and subscripting in Stata.

Who This Course is For"

Beginners to Stata who want a structured, hands-on overview of the platform.
Analysts, Researchers, and Students looking to expand their analytics toolkit with a robust, professional statistical package.
Professionals in academia, business, or government who need efficient methods for real-world data handling and interpretation.

Prerequisites:

No previous experience with Stata is required.
Some familiarity with basic statistics is helpful but not mandatory.
This course focuses on applying statistical methods in Stata rather than teaching pure statistical theory.

By mastering these essentials, you’ll be ready to tackle a wide variety of analytic challenges with confidence. Join me in The Essential Guide to Stata and take a major step forward in your data analytics journey!

Who this course is for:

Anyone wanting to work with Stata
Economics/Politics/Social Science students working with data
Those working in policy and government analysing data
Business managers using quantitative evidence

The Essential Guide to Stata

What you'll learn

Explore related topics

Course content

Introduction1 lecture • 2min

Getting Started6 lectures • 39min

Exploring Data7 lectures • 49min

Manipulating Data14 lectures • 1hr 32min

Visualising Data15 lectures • 1hr 52min

Testing Means, Correlations and ANOVA4 lectures • 26min

Linear Regression11 lectures • 1hr 50min

Categorical Choice Models3 lectures • 31min

Fractional/Proportional Variable Models1 lecture • 15min

Random Numbers and Simulation4 lectures • 24min

Requirements

Description

Who this course is for: