Business Analytics

Associate Professor

This course focuses on providing a range of practical skills that will develop their ability to effectively analyze, understand and present data in order to make informed business decisions. Utilizing MS Excel and SPSS software packages, students analyze real business data from a range of business case studies. Topics include types of data, data analysis and presentation, using central tendencies and dispersion to model business performance and risk, estimation techniques, a range of hypothesis tests including one sample, two sample and ANOVA testing, correlation analysis and regression analysis and forecasting.

Learning outcomes from the course:

  • Recognize common distinctions between quantitative and qualitative data and the limitations of such formulations
  • Identify key challenges in Research Design
  • Introduction to experimental controls and difference to that of data collected by observation and to the logic of random sampling and the importance of selection effects
  • Work on real word problem collect data and be competent with summary descriptive statistics such as: a mean, a median, a mode, and standard deviation
  • Be able to conduct graphical summaries of data and data visualization and usage of key measures of association and distinguish the appropriate use of correlation for nominal and interval data
  • Analyze tabular data of the kind commonly found in reports and understanding how data may be standardized for purposes of comparison. Being able to recognize trends and observe associations
  • Learn how to collect data using correct interviewing questions
  • Identify different survey formats and recognition of scales and scaling
  • Build an online survey to collect and analyze data using google forms and SPSS
  • Improve response rate of a survey study