Semester:
Spring of every year
Credits:
Total Credits: 1.5 Lecture/Recitation/Discussion Hours: 1.5
Prerequisite:
MKT 806 and MKT 819 or approval of department
Recommended Background:
MKT 805 or MBA 830
Restrictions:
Open to master's students in the Marketing Research major and open to MBA students in the Eli Broad College of Business and The Eli Broad Graduate School of Management or approval of department.
Description:
Statistical and computer based techniques for exploring and exploiting very large data arrays as common to large scale marketing and marketing research projects. Introduction to Statistical Package for the Social Sciences (SPSS), Statistical Analysis System (SAS) and other computer packages. Immersion in database, warehouse and mart customer relationship management (CRM) configurations.
Semester:
Spring of every year
Credits:
Variable from 1 to 3
Prerequisite:
MKT 806 and MKT 819 or approval of department
Recommended Background:
MKT 805 or MBA 830
Restrictions:
Open to master's students in the Business Analytics Major or in the Marketing Research major and open to MBA students in the Eli Broad College of Business and The Eli Broad Graduate School of Management or approval of department.
Description:
Statistical and computer based techniques for exploring and exploiting very large data arrays as common to large scale marketing and marketing research projects. Introduction to Statistical Package for the Social Sciences (SPSS), Statistical Analysis System (SAS) and other computer packages. Immersion in database, warehouse and mart customer relationship management (CRM) configurations.
Semester:
Spring of every year
Credits:
Variable from 1 to 3
Prerequisite:
MKT 854 or approval of department
Recommended Background:
MKT 805 or MBA 830
Restrictions:
Open to students in the Master of Business Administration in Business Administration or in the Marketing Research major or approval of department.
Description:
Statistical and computer-based techniques for exploring and understanding very large data arrays in large-scale marketing research projects. Understanding how advanced computer technology, large databases, and statistical methods such as predictive and classification models work together to generate new insights into marketing strategy issues. Emphasis on applications of using statistical analysis software.