Mathematics, Statistics & Data Science I

Course contents

- algebra: percentages; inequalities;
- linear and quadratic equations and functions; non-linear, exponential, logarithmic equations;
- differentiation rules; use of derivatives in analyzing functions;
- functions: properties of functions; polynomial, exponential, and logarithmic functions;
- linear systems: linear systems of two and more equations; Gauss-Jordan method; construc-tion of linear systems based on linguistically provided information;
- linear programming: graphical method; construction of LP problems based on linguistically provided information;
- probability theory: basic definitions; approaches to assigning probabilities; rules for compu-ting probabilities;
- combinatorics: general counting method; permutations; combinations

Department

Bachelor's program Business & Management