This unit provides students with the necessary foundations and skills to undertake second year units in business analytics and successfully complete the Business Analytics major. Theoretical models discussed are motivated by real life business applications and decision problems. The unit provides a grounding in linear algebra (matrix properties) and calculus and applies these methods to regression models with multiple variables. Topics covered include logistic regression, interaction and nonlinear effects. The unit also introduces the key ideas of optimization (particularly for quadratic problems) and shows how optimisation models can be used to make statistical estimates. At the same time as building understanding of the mathematical foundations needed in business analytics, the unit helps students to build programming skills to solve practical problems from the business area. The unit makes use of the modern programming languages such as Python.
1 x 2hr lecture and 1 x 2hr tutorial per week
assignment (30%), mid-semester exam (25%), final exam (45%)
BUSS1020 or DATA1001 or ECMT1010 or ENVX1001 or ENVX1002 or STAT1021 or ((MATH1005 or MATH1015) and MATH1115) or 6 credit points of MATH 1000-level units which must include MATH1905