22 Jun Introduction to Python for statistical data analysis
22/06/2020 - 25/06/2020
1:00 pm - 5:00 pm
statistics course | level: beginner
registrations and venue via Ghent University
THIS IS AN INTRODUCTORY COURSE FOR BEGINNERS WITH NO OR VERY LITTLE PYTHON-PROGRAMMING EXPERIENCE.
This course is intended as an Introduction to the Python programming language. In four afternoons, participants will build up the skills needed to import and manipulate data, construct descriptive statistics and plots, and perform basic analysis.
The course includes:
- Introducing the Python Anaconda distribution
- Types, Variables and Data Structures
- Functions, including writing your own
- Importing and exporting data
- Data manipulation with Numpy & Pandas
- Graphics with Matplotlib and Seaborn
- Basic statistical data analysis with scipy & statsmodels (i.e. descriptive analysis, statistical tests to compare groups, and linear regression)
!!! Bring your own laptop, with python.
Python is free and for this course you need to install the Anaconda distribution from https://www.anaconda.com/download/. It is recommended that you use Python version 3 or higher.
This course targets participants with little or no Python-programming experience who wish to start using Python for their data manipulation, data exploration or basic statistical analysis.
UGent - Campus Sterre - Building S9
Leslokaal 3.1 - S9 (3rd floor)
Krijgslaan 281, 9000 Gent
Dates & times:
Monday, 22 June 2020: 13h00 - 17h00
Tuesday, 23 June 2020: 13h00 - 17h00
Wednesday, 24 June 2020: 13h00 - 17h00
Thursday, 25 June 2020: 13h00 - 17h00
PhD's and postdocs of a Flemish university: 150*
Other academics: 150 €
Non-profit/Social sector: 250 €
Private sector: 500 €
*Note for UGent doctoral students: the course has been submitted for recognition to the UGent Doctoral Schools. Subject to approval, they can apply for reimbursement through an application of recognition with the UGent Doctoral Schools. Doctoral students from other Flemish universities can be reimbursed by FLAMES upon complete attendance.
No prior Python knowledge is required.
However, participants have to be familiar with basic statistical concepts as different measurement levels, measurements of centralization and variation, hypotheses testing and linear regression analysis. We will apply those techniques using Python, so you need to be able to understand these concepts.
Dr Jef Vlegels