Course description

Data Analytics with Programming

Introduction

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. Simulation techniques will be used to assess statistical tools.

Course content

  • Introduction to R. Introductory descriptive statistics, data visualization and data re-organization. Introductory statistical inference.
  • Data exploration and visualization in R.
  • An introduction to data-modelling: Simple regression models and an introduction to simulation.
  • Multiple linear regression: Dummy-variables, interaction terms, data-transformations and interpretation.
  • Regression diagnostics and model selection.

Learning outcome knowledge

Central theory surrounding regression models will be developed. The students will learn applied data analytics and programming using the R software system.

Exam organisation

  • Written assignment: 40%
  • Written exam: 60%