Applied Data Analytics

Introduction

This course gives an applied introduction to the most important techniques in business-related data analytics. Students are given hands-on experience using programming languages to work with data, using descriptive statistics to motivate models, and using models to turn data into actionable knowledge. Mathematical and statistical theory and applied data analysis will be interwoven into projects that the students will solve.
 

Course content

• An introduction to research design, cross-sectional studies, time-series, and longitudinal studies. 
• Introductory descriptive statistics, and their basic mathematical properties. Data visualization and data re-organization. Data exploration and visualization.
• A review of statistical inference and large sample inference using simulation-experiments.
• An introduction to statistical models. Simple regression models. An introduction to non-parametric trend estimates and traditional multiple linear regression modeling.
• Multiple linear regression: Dummy variables, interaction terms, data transformations and interpretation.

Disclaimer

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.