This course is organized by the Flanders' Training Network for Methodology and Statistics (FLAMES), on request of PhD students from the Faculty of Business Economics. It is open to people from all disciplines.
- This is a pratical introduction to Stata
- Assumes no/very little knowledge of Stata
- Learning objectives:
- Familiarize yourself with the Stata interface/managing do-files
- Get data in and out of Stata
- Explore and visualize data
- Screen and clean data (missing data/outlier handling)
- Compute new variables and transformations
- Basic statistical modeling
- Analysis of Variance
- Linear regression
- Logistic regression
- Exploratory factor analysis
- Confirmatory factor analysis
- Used in a variety of disciplines
- Great guides available on the web
Materials and setup
- Laptop users: you will need a copy of Stata installed on your machine
- Lab computer users: log in using your user name and password (to be supplied for external participants)
- Please feel free to ask questions at any point if they are relevant to the topic or the course as a whole.
- Collaboration with your neighbors is encouraged.
- If you are using a laptop, you will need to adjust paths accordingly.
- Make comments in your Do-file rather than on hand-outs.
- Save on flash drive or e-mail to yourself.
- Everyone interested in the topic - priority will be given to PhD students & postdocs affiliated to Flemish universities
- PhD students & postdocs of a Flemish university: €0 (free of charge)
- other academics: €300
- non-profit/social sector: €500
- private sector: €1.000
- 30 places available
- November 18-19-20-21-22, 2019 - 9:00-16:00
- You are expected to attend all five days.
- A sandwich lunch will be provided.
- Campus Diepenbeek, Building D, room B17
- Closed since November 4, 2019.
- Please cancel your registration at least two weeks in advance if you cannot make it (cf. FLAMES cancellation & no-show policy).
- DS BSH: category 'advanced discipline-specific knowledge' - domain-specific course at PhD level (active)
- DS HLS: category 'scientific skills' - one compulsory elective technical course
- DS ST: category 'seminars & advanced courses' - one advanced course