Jonas Dix
Vita
EDUCATION
2023 – present: Research Associate and PhD Candidate (Institute of Economics, Leuphana University Lueneburg, Germany)
2020 – 2023: M. Sc. in Public Economics (Free University of Berlin, Germany)
- Master’s thesis: „Ethnic Discrimination in Access to Health Care Services: A Field Experiment“
- Research assistant at WZB Berlin Social Science Center in the research projects: „Social inequality and disparities in political participation: Is ill health a missing link?“ and „Social and ethnic inequalities in access to healthcare: a field experiment“
2017 – 2020: B. Sc. in Economics (Leuphana University Lueneburg, Germany)
- Bachelor’s thesis: „A field experiment on ethnic discrimination in the Berlin rental market“
- Scholarship awarded by the Federal State of Lower Saxony
- Student assistant at the Institute of Economics
WORK EXPERIENCE
2022: Federal Ministry for Economic Affairs and Climate Action (Berlin, Germany)
- Intern, Department VI: Digital and Innovation Policy
2016 – 2017: Voluntary Social Year (Malawi)
Courses
⌄
Building on the lecture Mathematics for Business and Economics, this course provides an overview of essential concepts in multivariate analysis and linear algebra.
Contents:
I. Linear Algebra
1. Solving Linear Systems
2. Vectors and Linear Independence
3. Vector Spaces and Linear Spaces
4. Linear Mappings and Matrices
5. Inverse, Determinant, and Definiteness of a Matrix
II. Analysis
6. Total Derivative and Differential of a Function
7. Implicit Functions
Contents:
I. Linear Algebra
1. Solving Linear Systems
2. Vectors and Linear Independence
3. Vector Spaces and Linear Spaces
4. Linear Mappings and Matrices
5. Inverse, Determinant, and Definiteness of a Matrix
II. Analysis
6. Total Derivative and Differential of a Function
7. Implicit Functions
⌄
The course covers essential methods of inductive statistics that are used to draw conclusions from a data sample about the underlying population.
Outline:
1. Introduction
2. Probability and stochastics
3. Discrete random variables
4. Continuous random variables
5. Multivariate random variables
6. Estimation of parameters
7. Hypothesis testing
8. Regression analysis
Outline:
1. Introduction
2. Probability and stochastics
3. Discrete random variables
4. Continuous random variables
5. Multivariate random variables
6. Estimation of parameters
7. Hypothesis testing
8. Regression analysis