Course Description
Through a series of case studies, students learn to leverage data analysis to support the discovery of meaningful customer targets for a program, service, or product and to guide the design of such initiatives through iterative testing.
Additional Requirements for Graduate Students:
Graduate students will prepare a detailed written report (8 to 10
pages) outlining the method, reporting the results of the a
analyses, and discussing the implications and limitations of the
study findings with references to supporting academic literature.
Athena Title
Cons An Evidence Based Innov
Undergraduate Prerequisite
Permission of department
Graduate Prerequisite
Permission of department
Semester Course Offered
Offered spring
Grading System
A - F (Traditional)
Course Objectives
To establish the student’s analytical skills in the areas of factor analysis, cluster analysis, concept testing, experimental design, and conjoint design. To expand the student’s set of tools capable of executing and delivering on statistical analysis. To build the student’s vocabulary for evidence-based storytelling with creative, innovative audiences.
Topical Outline
Course Overview Tools and Data Team Strengths and Focus Introducing the Tools: SPSS and Tableau Overview Latent Constructs Introduction to Factor Analysis Discovering the Factors Confirming the Factors Describing Your Results Using the Factors Meaningful Groups Introduction to Cluster Analysis The Cluster Solutions The Cluster Solution Story Using Your Clusters Preferences and Predictions Introduction to Conjoint Design and Concept Testing Analyzing Results: The Concept Test Analyzing Results: The Conjoint Design Application to Your Project: Concept Test Plans Application to Your Project: Conjoint Design Plans Putting It All Together
Syllabus