S414 Advanced Mathematical Methods
| Lecturer | Dr. Julie Schnaitmann |
| Profiles | recently enrolled Master students The course is open for CIVIS students. |
| Language | English |
| Sessions | 04 October 2023, 9.00 am - 12.00 pm - Linear Algebra I 06 October 2023, 9.00 am - 12.00 pm - Calculus 09 October 2023, 9.00 am - 12.00 pm - Mathematical Statistics 10 October 2023, 9.00 am - 12.00 pm - Parameter Estimation 12 October 2023, 9.00 am - 12.00 pm - Hypothesis Testing |
| Place | room: HS 10, Neue Aula |
| Credit points | 3 ECTS |
| Registration | no registration required to take part in the course |
| Exam (60 min) | tba |
| Q&A - Session befor the exam | tba |
Format of the Lecture
The lecture takes place in person. If you cannot attend the lecture on site, the slides and the audio from last year's lecture are uploaded to the virtuv server.
Content
This course is designed for recently enrolled Master students at the School of Business and Economics. The aim is to provide participants with fundamentals of mathematics, probability theory, and statistics which are particularly important in the first semester of the Master program. The course program covers key concepts of basic probability theory, basics of statistical inference, a summary of matrix algebra (e.g., matrix addition and matrix multiplication, eigenvalues), differentiation and integration.
Literature (selected chapters)
- Hamilton, J. D., Time Series Analysis
- Lovric, M., Vector Calculus
- Marsden, J. E. & Tromba, A. J., Vector Calculus
- Papoulis, A. & Pillai, A. U., Probability, Random Variables and Stochastic Processes
- Sotskov, Y.N. & Werner, Frank, Mathematics for Economics and Business, LINK
- Sydsaeter, K. & Hammond, P., Essential Mathematics for Economic Analysis
- Sydsaeter, K.; Hammond, P.; Seierstad, A. & Strøm, A., Further Mathematics for Economic Analysis
Short summaries:
- Greene, William H., Econometric Analysis, edition 5 or more recent, appendices A and B
- Wooldridge, Jeffrey M., Introductory Econometrics, 4th or 5th edition, appendices B, C, D.
Course Material
The course is designed as a refresher. You find links to video lectures on the slides.
PART ONE:
Chapter 1 Linear Algebra part I, Exercises_01
Chapter 1 Linear Algebra part II, Exercises_02
Chapter 2 Multivariate Calculus, Exercises_03
Chapter 3 Integral Calculus, Exercises_04
PART TWO:
Chapter 4 Mathematical Statistics part I, Exercises_06
Chapter 4 Mathematical Statistics part II, Exercises_06
Chapter 5 Parameter Estimation, Exercise 09
Chapter 6 Hypothesis testing, Exercises_07
25 Easy pieces in Mathematical Statistics
You find all materials, including videos which provide solutions guidelines to the exercise, at the Open-ILIAS platform at:
https://vitruv.uni-tuebingen.de/ilias3/goto_pr01_crs_7244.html
eLearning for math repetition:
https://vitruv.uni-tuebingen.de/ilias3/goto_pr01_crs_4803.html