The course “Introduction to Stata Programming for Social Science Data Analysis” is a comprehensive program that covers the fundamentals of using Stata as a powerful data analysis software package. As the developer and instructor of this course, I have designed it to provide students with the necessary skills to navigate and utilize Stata effectively for data analysis.

The course begins with an introduction to Stata, familiarizing students with the software’s interface and functionalities. Students learn how to read and prepare data within Stata, ensuring that datasets are properly formatted and ready for analysis. Data management techniques are also covered, equipping students with skills to manipulate and clean datasets.

Descriptive statistics, both univariate and bivariate, are explored in the course. Students gain an understanding of how to summarize and analyze data using various statistical measures. They also learn how to visualize data effectively, employing graphs and charts to gain insights into patterns and relationships within the data.

Measures of association for contingency tables are introduced, allowing students to assess the relationships between categorical variables. Statistical tests are covered, providing students with the knowledge and tools to perform hypothesis testing and assess the significance of results.

Regression analysis is a key component of the course, including simple and multiple linear regression, logistic and probit regression. Students learn how to build regression models, interpret coefficients, assess model fit, and conduct regression diagnostics. They also explore advanced topics such as marginal effects, interaction effects, and squared effects, enhancing their understanding of regression analysis.

Throughout the course, students engage in hands-on exercises and practical examples, allowing them to apply their knowledge and reinforce their programming skills using Stata.

By the end of the course “Introduction to Stata, Programming Using Stata,” students are equipped with the necessary skills to conduct data analysis, perform statistical tests, and build regression models using Stata. This course serves as a valuable foundation for individuals interested in utilizing Stata for their research, analysis, and data management tasks.

Table of Contents

• Introduction to Stata as a data analysis software package
• Reading and preparing data
• Data Management
• Descriptive statistics (univariate / bivariate)
• Visualizing data
• Measures of association for contingency tables
• Statistical tests
• Regression analysis (simple and multiple linear regression, logistic and probit regression, regression diagnostics, marginal effects, interaction and squared effects)