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Daugiamatė statistika (GRAV007)

Course Annotation

There are always key decisions to make at the heart of a superior marketing practice.  A marketer, for example, must decide on how to price a specific product, which types of distribution channels would be most appropriate or most effective, and/or how to advertise the given product most effectively.  In order to minimize complexity and to select and support the best alternative from a multitude, quantitative marketing methods and multivariate data analysis have become essential to the success of most business organizations.  Thus, the key purpose of this course is to acquire a general and fundamental understanding of the various quantitative and analytics tools that can be utilized and applied to a variety of diverse marketing settings.  This course will combine a theoretical foundation based on lectures and readings with practical applications to assist students in acquiring a sound working knowledge of and essential experience with multivariate data analysis.

Course Goal

The main objective of the course is to assist students in acquiring a sound working knowledge of multivariate data analysis tools, methods and applications.  Any business manager who examines only two-variable or bivariate relationships (and avoids multivariate analysis) is ignoring a larger set of powerful tools that often provide additional useful information and critical business insights.  The conceptual framework and methodologies of various multivariate data analysis tools will be illustrated by numerous cases and examples.  The emphasis here is on when to apply given tools and methods and how to interpret obtained results – utilizing R and Matlab.  All in-coming students should already have a fundamental understanding of basic introductory statistics.

Learning Outcomes

  • Identify business situations where multivariate statistics could be applied.
  • Demonstrate knowledge and understanding of the different multivariate data analysis methods most commonly used in business.
  • Understand how to use statistical methods for decision-making.
  • Analyse data, interpret results and present them in a rigorous, yet understandable, clear and concise manner.
  • Demonstrate analytical skills and presentation skills for understanding, analysing and debating business cases. 
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