The Complete Guide to Stata from Udemy

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The Complete Guide to Stata

Learning and applying new statistical techniques can be daunting experience.

This is especially true once one engages with “real life” data sets that do not allow for easy “click-and-go” analysis, but require a deeper level of understanding of programme coding, data manipulation, output interpretation, output formatting and selecting the right kind of analytical methodology.

In this course you will receive a comprehensive introduction to Stata and its various uses in modern data analysis. You will learn to understand the many options that Stata gives you in manipulating, exploring, visualizing and modelling complex types of data. By the end of the course you will feel confident in your ability to engage with Stata and handle complex data analytics. The focus of each session will consistently be on creating a “good practice” and emphasising the practical application – and interpretation – of commonly used statistical techniques without resorting to deep statistical theory or equations.

This course consists of three sub-courses that will 1) teach you the essentials of Stata 2) provide you with tips and tricks for Stata and 3) teach you advanced data visualization techniques.

No prior engagement with is Stata needed. Some prior statistics knowledge will help but is not necessary.

The course is aimed at anyone interested in data analytics using Stata.

Like for other professional statistical packages the course focuses on the proper application - and interpretation - of code.

Some basic quantitative/statistical knowledge will be required; this is not an introduction to statistics course but rather the application and interpretation of such using Stata.

Topics covered include:

Getting started with Stata
Viewing and exploring data
Manipulating data
Visualising data
Correlation and ANOVA
Regression including diagnostics (Ordinary Least Squares)
Regression model building
Hypothesis testing
Binary outcome models (Logit and Probit)
Fractional response models (Fractional Logit and Beta Regression)
Categorical choice models (Ordered Logit and Multinomial Logit)
Simulation techniques (Random Numbers and Simulation)
Count data models (Poisson and Negative Binomial Regression)
Survival data analysis (Parametric, Cox-Proportional Hazard and Parametric Survival Regression)
Panel data analysis (Long Form Data, Lags and Leads, Random and Fixed Effects, Hausman Test and Non-Linear Panel Regression)
Difference-in-differences analysis (Difference-in-Difference and Parallel Trends)
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 (Sample Size, Power Size and Effect Size)
Matrix operations (Matrix operators, Matrix functions, Matrix subscripting)

There are also 125 tips and tricks for Stata. These tips are aimed at helping you become a Stata master. They cover a wide range of issues the following topics:

Data management
Graphing
Statistics
Programming.

Each tip is designed to be stand-alone and will take no more than 2 minutes.

Finally, you will be shown some of the most important data visualization methods and learn what ae the advantages and disadvantages of each technique are. A wide variety of graphs are highlighted in great detail including:

Histograms
Density plots
Spike plots
Rootograms
Box plots
Violin plots
Stem-and-Leaf plots
Quantile plots
Bar graphs
Pie charts
Dot charts
Radar plots
Scatter plots
Heat plots
Hex plots
Sunflower plots
Lines of best fit
Area plots
Line plots
Range plots
Rainbow plots
Jitter plots
Table plots
Baloon plots
Mosaic plots
Chernoff faces
Sparkling plots
Bubble plots
and more

Depending on your desired learning outcomes you may wish to focus on specific parts.

To gain a basic understanding of Stata watch sections 2, 3, 4, 5, 6, 7 and 8
To learn advanced Stata concepts watch sections 8, 9, 10, 11, 12, 13, 14, 15, 16 and 17
To learn fast tips for Stata watch sections 18, 19, 20 and 21
To learn all about data visualisation in Stata watch sections 5, 21, 22, 23, 24, 25 and 26
To learn data management concepts watch sections 3, 4 and 18

What's inside

Learning objectives

An essential introduction to stata
Data manipulation in stata
Data analysis in stata
Regression modelling
Stata code
Advanced stata code
Fast, and to the point, useful tips to use in stata
Data management

Programming
Graphics
Statistics
Basic plot types
Intermediate plot types
Advanced plot types
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An essential introduction to stata
Data manipulation in stata
Data analysis in stata
Regression modelling
Stata code
Advanced stata code
Fast, and to the point, useful tips to use in stata
Data management
Programming
Graphics
Statistics
Basic plot types
Intermediate plot types
Advanced plot types
Show more
Show less

Syllabus

Introduction

Learn the basics of the Stata interface

The Stata Interface

Using Help in Stata

Command Syntax

.do and .ado Files

Log Files

Importing Data

Learn the basics of how to explore data

Viewing Raw Data

Describing and Summarizing

Tabulating and Tables

Missing Values

Numerical Distributional Analysis

Using Weights

The New Table Command (Stata 17)

Learn how to manipulate and recode data

Recoding an Existing Variable

Creating New Variables, Replacing Old Variables

Naming and Labelling Variables

Extensions to Generate

Indicator Variables

Keep and Drop Data/Variables

Saving Data

Converting String Data

Combining Data

Using Macro's and Loop's Effectively

Accessing Stored Information

Multiple Loops

Date Variables

Subscripting over Groups

Learn basic data visualisation

Graphing in Stata

Bar Graphs and Dot Charts

Graphing Distributions

Pie Charts

Scatterplots and Lines of Best Fit

Graphing Custom Functions

Contour Plots (and Interaction Effects)

Jitter Data in Scatterplots

Sunflower Plots

Combining Graphs

Changing Graph Sizes

Graphing by Groups

Changing Graph Colours

Adding Text to Graphs

Scatterplots with Categories

Learn how to test means and correlations

Association Between Two Categorical Variables

Testing Means

Bivariate Correlation

Analysis of Variance (ANOVA)

Learn the basics of regression analysis

Ordinary Least Squares (OLS) Regression

Factor Variables in OLS Regression

Diagnostic Statistics for OLS Regression

Log Dependent Variables and Interaction Effects in OLS Regression

Hypothesis Testing in OLS Regression

Presenting Estimates from OLS Regression

Standardizing Regression Estimates

Graphing Regression Estimates

Oaxaca Decomposition Analysis

Mixed Models: Random Intercepts and Random Coefficients

Constrained Linear Regression

Learn how to perform non-linear regression

Binary Choice Models (Logit/Probit Regression)

Diagnostics and Interpretation of Logit and Probit Regression

Ordered and Multinomial Choice Models

Fractional Logit, Beta Regression and Zero-inflated Beta Regression

Learn how to simulate with random numbers

Random Numbers

Data Generating Process

Simulating a Violation of Statistical Assumptions

Monte Carlo Simulation

Learn about count regression models

Features of Count Data

Poisson Regression

Negative Binomial Regression

Truncated and Censored Count Regression

Hurdle Count Regression

Learn about survival data analysis

What is Survival Analysis?

Setting up Survival Data

Descriptive Statistics in Survival Data

Non-parametric Survival Analysis

Cox Proportional Hazard's Model

Diagnostics for Cox Models

Parametric Survival Analysis

Learn about panel data analysis

Setting up Panel Data

Panel Data Descriptives

Lags and Leads

Linear Panel Estimators

The Hausman Test

Non-Linear Panel Estimators

Learn how to run DiD models

Difference-in-Differences Estimation

Parallel Trend Assumption

Difference-in-Differences without Parallel Trends

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Suitable for learners interested in data analytics using Stata.

Provides the fundamentals of Stata without assuming prior knowledge.

Emphasizes practical application of Stata for complex data analysis.

Covers a comprehensive range of statistical techniques, including advanced topics in regression modeling, survival analysis, and panel data analysis.

Includes sections on data management, programming, statistics, and graphics to provide a well-rounded foundation

Guided by F. Buscha, a respected instructor in the field of data analysis using Stata.

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in The Complete Guide to Stata with these activities:

Review Basic Statistical Concepts

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This course builds on basic statistical concepts. Refreshing this knowledge will ensure a solid foundation for the course material.

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Review concepts such as probability, hypothesis testing, and confidence intervals
Practice solving statistical problems
Consult online resources or textbooks for additional support

Review Statistical Concepts

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A strong foundation in statistical concepts is necessary for understanding and applying statistical methods.

Browse courses on Quantitative Reasoning

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Review basic probability and probability distributions
Practice calculating descriptive statistics
Practice conducting hypothesis tests

Explore Stata Tutorial Resources

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Numerous resources and tutorials are available online to help you learn Stata at your own pace.

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Search for tutorials on specific Stata topics
Follow along with the tutorials and practice the commands
Consult the Stata documentation for additional guidance

Five other activities

Expand to see all activities and additional details

Show all eight activities

Practice Data Manipulation with Stata

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Gaining proficiency in data manipulation using Stata is essential for preparing and analyzing statistical data.

Browse courses on Data Manipulation

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Load and explore a dataset
Practice creating new variables
Practice combining and merging datasets

Build a Stata Cheat Sheet

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A cheat sheet can serve as a quick reference for commonly used Stata commands, making it easier to navigate the software during data analysis.

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Identify commonly used commands
Summarize the syntax and usage of each command
Organize the commands by category or topic

Develop a Research Proposal

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A research proposal helps you define your research objectives, methodologies, and expected outcomes, which will guide your data analysis throughout the course.

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Identify a research topic and develop a research question
Review relevant literature
Develop a hypothesis or research plan
Write up your proposal

Develop a Data Analysis Plan

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Creating a data analysis plan helps organize your thoughts and plan your analysis, ensuring that you are using the most appropriate methods for your research questions.

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Define your research questions and objectives
Gather and explore your data
Choose the appropriate statistical methods
Write up your plan

Participate in a Stata Discussion Group

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Engaging with peers can facilitate learning, provide support, and expose you to diverse perspectives on Stata.

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Join a relevant discussion group
Participate in discussions and ask questions
Share your knowledge and experience

Career center

Learners who complete The Complete Guide to Stata will develop knowledge and skills that may be useful to these careers:

Data Scientist

A Data Scientist is responsible for preparing and cleaning data, building and evaluating machine learning models, and communicating insights to stakeholders. The Complete Guide to Stata course can help you develop the skills needed to succeed in this role by providing you with a comprehensive understanding of Stata, a powerful statistical software package. You will learn how to use Stata to manipulate, explore, visualize, and model complex data. This course will also teach you how to interpret and communicate your findings effectively.

See salaries and explore the career path for Data Scientist

Statistician

A Statistician is responsible for collecting, analyzing, and interpreting data. They use their skills to help businesses and organizations make informed decisions. The Complete Guide to Stata course can help you develop the skills needed to succeed in this role by providing you with a comprehensive understanding of Stata, a powerful statistical software package. You will learn how to use Stata to manipulate, explore, visualize, and model complex data. This course will also teach you how to interpret and communicate your findings effectively.

See salaries and explore the career path for Statistician

Data Analyst

A Data Analyst is responsible for collecting, cleaning, and analyzing data to identify trends and patterns. They use their skills to help businesses and organizations make informed decisions. The Complete Guide to Stata course can help you develop the skills needed to succeed in this role by providing you with a comprehensive understanding of Stata, a powerful statistical software package. You will learn how to use Stata to manipulate, explore, visualize, and model complex data. This course will also teach you how to interpret and communicate your findings effectively.

See salaries and explore the career path for Data Analyst

Market Researcher

A Market Researcher is responsible for conducting research to understand the needs and wants of consumers. They use their findings to help businesses develop new products and services. The Complete Guide to Stata course can help you develop the skills needed to succeed in this role by providing you with a comprehensive understanding of Stata, a powerful statistical software package. You will learn how to use Stata to manipulate, explore, visualize, and model complex data. This course will also teach you how to interpret and communicate your findings effectively.

See salaries and explore the career path for Market Researcher

Business Analyst

A Business Analyst is responsible for analyzing business processes and identifying opportunities for improvement. They use their skills to help businesses make better decisions and achieve their goals. The Complete Guide to Stata course can help you develop the skills needed to succeed in this role by providing you with a comprehensive understanding of Stata, a powerful statistical software package. You will learn how to use Stata to manipulate, explore, visualize, and model complex data. This course will also teach you how to interpret and communicate your findings effectively.

See salaries and explore the career path for Business Analyst

Financial Analyst

A Financial Analyst is responsible for analyzing financial data to make investment recommendations. They use their skills to help businesses and individuals make informed financial decisions. The Complete Guide to Stata course can help you develop the skills needed to succeed in this role by providing you with a comprehensive understanding of Stata, a powerful statistical software package. You will learn how to use Stata to manipulate, explore, visualize, and model complex data. This course will also teach you how to interpret and communicate your findings effectively.

See salaries and explore the career path for Financial Analyst

Operations Research Analyst

An Operations Research Analyst is responsible for using mathematical and statistical techniques to solve business problems. They use their skills to help businesses improve their efficiency and productivity. The Complete Guide to Stata course can help you develop the skills needed to succeed in this role by providing you with a comprehensive understanding of Stata, a powerful statistical software package. You will learn how to use Stata to manipulate, explore, visualize, and model complex data. This course will also teach you how to interpret and communicate your findings effectively.

See salaries and explore the career path for Operations Research Analyst

Quantitative Researcher

A Quantitative Researcher is responsible for using mathematical and statistical techniques to analyze financial data. They use their skills to help investment firms make informed investment decisions. The Complete Guide to Stata course can help you develop the skills needed to succeed in this role by providing you with a comprehensive understanding of Stata, a powerful statistical software package. You will learn how to use Stata to manipulate, explore, visualize, and model complex data. This course will also teach you how to interpret and communicate your findings effectively.

See salaries and explore the career path for Quantitative Researcher

Actuary

An Actuary is responsible for assessing and managing financial risk. They use their skills to help businesses and individuals make informed financial decisions. The Complete Guide to Stata course can help you develop the skills needed to succeed in this role by providing you with a comprehensive understanding of Stata, a powerful statistical software package. You will learn how to use Stata to manipulate, explore, visualize, and model complex data. This course will also teach you how to interpret and communicate your findings effectively.

See salaries and explore the career path for Actuary

Epidemiologist

An Epidemiologist is responsible for investigating the causes and spread of disease. They use their skills to help prevent and control outbreaks of disease. The Complete Guide to Stata course can help you develop the skills needed to succeed in this role by providing you with a comprehensive understanding of Stata, a powerful statistical software package. You will learn how to use Stata to manipulate, explore, visualize, and model complex data. This course will also teach you how to interpret and communicate your findings effectively.

See salaries and explore the career path for Epidemiologist

Software Engineer

A Software Engineer is responsible for designing, developing, and testing software applications. They use their skills to create software that meets the needs of users. The Complete Guide to Stata course may be useful for Software Engineers who want to develop software for statistical analysis. This course will teach you how to use Stata to manipulate, explore, visualize, and model complex data.

See salaries and explore the career path for Software Engineer

Data Engineer

A Data Engineer is responsible for building and maintaining data pipelines. They use their skills to ensure that data is accurate, consistent, and accessible. The Complete Guide to Stata course can help Data Engineers develop the skills needed to work with statistical data. This course will teach you how to use Stata to manipulate, explore, visualize, and model complex data.

See salaries and explore the career path for Data Engineer

Machine Learning Engineer

A Machine Learning Engineer is responsible for building and deploying machine learning models. They use their skills to help businesses make better decisions. The Complete Guide to Stata course may be useful for Machine Learning Engineers who want to develop machine learning models for statistical analysis. This course will teach you how to use Stata to manipulate, explore, visualize, and model complex data.

See salaries and explore the career path for Machine Learning Engineer