Data Visualization in Stata
What you'll learn
- Data visualisation
- Graphing in Stata
- Basic plot types
- Intermediate plot types
- Advanced plot types
- Distribution plots
- Relationship plots
- Categorical plots
- Specialised plots
- Stata code
- Advanced Stata code
- Basic Stata knowledge
- Basic Stata coding (.do files, commands, varlists and options)
Make sure to check out my twitter feed for monthly promo codes and other updates (@easystats3)
Learning and applying new visual techniques can often be a daunting experience. This is especially true if you need to generate and code data visualizations yourself.
This course is designed to provide you with a compact, and easy to understand, set of videos that focus on the basic principles behind many common data visualization and how you can code them in Stata.
The course is modular; just click on the graphs that you are most interested in and learn away. You do not need to follow this course linearly.
This course will teach you many different methods to visualize data and how to generate these yourself in Stata
Visualizing and graphing data is a vital in modern data analytics. Whether you are a data scientist, student of quantitative methods or a business user, having an understanding of how to visualise data is an important aspect in getting data information across to other stakeholders. Many different ways of visualising data have been devised and some are better than other. However, each method has advantages and disadvantages and having a solid understanding of what visualization might be best suited is key to delivering a concise and sharp "data message".
Often, it takes years of experience to accumulate knowledge of the different graphs and plots. In these videos, I will outline some of the most important data visualization methods and explain, without any equations or complex statistics, what are the advantages and disadvantages of each technique.
I will also demonstrate how each graph can be created, modified and customised in Stata.
The main learning outcomes are:
To learn and understand the basic methods of data visualization
To learn, in an easy manner, variations and customisations of basic visualization methods
To gain experience of different data visualization techniques and how to apply them
To learn and code many Stata graphs
To gain confidence in your ability to modify and create bespoke data visualisations in Stata
Please note the following: You should have some understanding of how Stata works and what .do files are. If you are totally new to Stata you should take a look at my "Essential Guide To Stata" course that explains Stata from the ground up. This course focuses specifically on how to create many different types of graphs and all their possible options and sub-options.
Specific themes include:
Lines of best fit
Who this course is for:
- Stata users
- Data analysts
- Data scientists
- Quantitative degree students
- Quantitative business users
- Economists, Social Scientists, Political Scientists, Biostatisticians, and other disciplines
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.