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, general approaches of parameter estimation (e.g., ordinary least squares), a summary of matrix algebra (e.g., matrix addition and matrix multiplication, eigenvalues), differentiation and integration, and difference equations.

• 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
• 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.

Further literature (as requested in the first zoom session):

• Sotskov, Y.N. & Werner, Frank, Mathematics for economics and business, LINK