This course gives an applied introduction to the most important techniques in business-related data analytics. Students are given hands-on experience with programming, working with data, using descriptive statistics to motivate models, and using models to turn data into actionable knowledge. Programming, mathematical theory and applications will be interwoven in application focused projects.
- Introduction to sums and summation notation, and other foundational issues.
- Introduction to R. Introductory descriptive statistics, data visualization and data re-organization. Data exploration and visualization in R
- A/B testing, and a review of statistical inference via testing for a proportion (exact theory), a brief review of large sample inference, and an introduction to the bootstrap
- An introduction to data-modelling: Simple regression models and an introduction to simulation.
- Multiple linear regression: Dummy-variables, interaction terms, data-transformations and interpretation.
- Simulation and out of sample forecasts.
- Regression diagnostics and model selection.
This is an excerpt from the complete course description for the course. If you are an active student at BI, you can find the complete course descriptions with information on eg. learning goals, learning process, curriculum and exam at portal.bi.no. We reserve the right to make changes to this description.