The Course covers a comprehensive introduction to Stata and its various uses in modern data management and analysis. You will understand the many options that Stata gives you in manipulating, exploring, visualising 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. No prior engagement with is Stata needed. Some prior statistics knowledge will help but is not necessary.

Like for other professional statistical packages the course focuses on the proper application – and interpretation – of code. Some basic quantitative/statistical knowledge will be require since 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)