Website of Professor Dr. (UoP) Bernd Heesen



Organizations across the world are increasingly relying on business analytics and statistics to help them look for latent information revealed through data analysis. An example could be to check the credit worthiness (with objectivity) of an individual using a set of parameters before the issuance of a credit card. Though there could be variations of an individual’s parameter from the standard, data analysis and hypotheses testing would reveal whether the difference/deviation is significant.
At the end of the course, students will be familiar with the use of data analysis and statistics for decision making in business.

The Learning objectives are to:

  • Understand the application of statistical methods (descriptive, predictive, prescriptive) in analyzing and interpreting data.
  • Understand how to present and display data to convey meaning.
  • Prepare and code data for statistical analysis.
  • Test hypotheses using statistical software.
  • Derive inferences from the results of statistical tests and make meaningful conclusions from the tested hypotheses.
  • Learn to use statistical software tools for analyses, machine learning and artificial intelligence:
    • R
    • Microsoft Excel