Through a series of case studies, students learn to leverage data
analysis to drive strategic decisions via the telling of a
compelling, evidence-based story.
Additional Requirements for Graduate Students: Graduate students will design, conduct, and deliver an
additional solo project for which the student identifies the
question, locates and prepares the data, conducts the analysis,
and delivers a written report of the methods, results, and
implications.
Athena Title
Cons An Evidence Based Strateg
Equivalent Courses
Not open to students with credit in FHCE 4000S or FHCE 6000S
Undergraduate Pre or Corequisite
STAT 2000 or STAT 2000E or STAT 2010 or STAT 2100H or MSIT 3000 or MSIT 3000E or MSIT 3000H or BUSN 3000 or BUSN 3000E or BUSN 3000H
Semester Course Offered
Offered fall and spring
Grading System
A - F (Traditional)
Student learning Outcomes
Students will understand the move from an organizational need to the right question(s) and analytical plan to support the need.
Students will find, extract, organize, and describe the data required.
Students will develop spreadsheet models to analyze data, evaluate risk, and optimize strategic decisions.
Students will identify, quantify, and interpret relationships between variables.
Students will craft effective, fact-based stories that inspire conversation and action.
Students will present and justify a course of action to those who can take action.
Students will complete analytical projects for real and fictitious clients identifying analytical projects that would support the decisions their client is trying to make and the analyses that would support those decisions.
Students will learn to blend left and right-brain thinking into a compelling, evidence-based story with creative and supported recommendations for action.
Topical Outline
Case 1: Learning the Process
Getting to the Question
Preparing the Data
Commands and Methods
Descriptive Statistics
Bivariate Analysis (Crosstabs, Correlations, T-Tests)
Multivariate Analysis (Regression)
Storytelling
Case 2: Mastering the Process
Getting to the Question
Commands and Methods
Descriptive Statistics
Bivariate Analysis (Crosstabs, Correlations, T-Tests)
Multivariate Analysis (Regression)
Storytelling
Case 3: Flying Solo
Getting to the Question
Preparing the Data
Commands and Methods
Descriptive Statistics
Bivariate Analysis (Crosstabs, Correlations, T-Tests)
Multivariate Analysis (Regression)
Storytelling
Case 4: Expert Storytelling
The Language of Data Science
Institutional Competencies Learning Outcomes
Analytical Thinking
The ability to reason, interpret, analyze, and solve problems from a wide array of authentic contexts.
