The Essential Guide to Stata
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
- Instrumental Variables
- Power Analysis
- There are no requirements
Make sure to check out my twitter feed for monthly promo codes and other updates (@easystats3).
The Essential Guide to Data Analytics with 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 will focus on providing an overview of data analytics using Stata.
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
Correlation and ANOVA
Regression including diagnostics (Ordinary Least Squares)
Regression model building
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)
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
Check out my twitter feed for regular promo codes.
Franz is a Professor of Economics at the University of Westminster. Franz joined the University of Westminster in 2006 after completing his PhD in Economics at Lancaster University.
Franz's personal research interests are in education economics, labor economics, and applied econometrics. Franz has made scientific contributions to issues such as social mobility, measuring the returns to education, the effect of weather of happiness and identity formation. He has been involved in numerous funded research projects from research councils and government departments.
Franz has contributed to wide range of projects including policy evaluation and bespoke econometric advice to UK government departments. These include the Ministry of Defence, HM Revenue and Customs, the Department for Education and the Department for Business, Innovation and Skills.
He has published in leading journals such as Economics of Education Review, the Oxford Bulletin of Economics and Statistics, the British Journal of Political Science and the British Journal of Sociology. Franz has also contributed to numerous policy reports and his research has been covered by media outlets such as BBC news, BBC Radio 4, The Economist, The Guardian, The Times, and Huffington Post. Franz also has a monthly radio program called Policy Matters on Share Radio.
Franz is an experienced online educator and has published several online courses including LinkedIn Learning.