Data Analysis II
Vrije Universiteit Amsterdam
Amsterdam, The Netherlands
Area of Study
Computer Programming, Statistics
Taught In English
Course Level Recommendations
ISA offers course level recommendations in an effort to facilitate the determination of course levels by credential evaluators.We advice each institution to have their own credentials evaluator make the final decision regrading course levels.
Recommended U.S. Semester Credits3
Recommended U.S. Quarter Units4
Hours & Credits
The student further explores the fields of statistics, data science and econometrics, and also obtains first skills of programming in Python.
Attention is given to how methods are implemented in a matrix-oriented software environment. A case study on the house prices in Amsterdam is carried out and the student learns how to present empirical results.
- Analyse large data sets and make predictions using statistical models
- Learn how to apply software implementations in a matrix-oriented environment
- Learn how to present results: written reports and presentations.
- Learn how to work in a group of students.
- Self-reflection: reflect on choice for Bachelor Econometrics & Data Science, reflect on first year of Bachelor Econometrics & Data Science
Lectures, practicals, question hours
TYPE OF ASSESSMENT
Assignments and presentations.
RECOMMENDED BACKGROUND KNOWLEDGE
Knowledge of calculus, probability and statistics
Courses and course hours of instruction are subject to change.
Some courses may require additional fees.