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MGNT 333

MGNT 333: Business Analytics for Decision Making

Prerequisite: Junior standing, STAT 200, and MATH 125, MATH 126, MATH138, MATH 151, MATH 169, MATH 171 or MATH 168.

Credit hours (3)


Develops skills for applying descriptive, predictive, and prescriptive statistical models to assist decision makers with solving business problems. The course is a core requirement for all business majors.

Note(s): Scientific and Quantitative Reasoning designated course.


Detailed Description of Course

Outline of Major Topics:
    1) Descriptive Analytics including
        a. Data visualization
        b. Descriptive Statistics
        c. Probability Distributions
        d. Statistical Inferences
    2) Predictive Analytics including
        a. Forecasting Models
        b. Regression Analysis
        c. Simulation Analysis
    3) Prescriptive Analytics including
        a. Linear Programming Models
        b. Project Management
        c. Inventory Management


Detailed Description of Conduct of Course

Lectures are designed to demonstrate to an audience with diverse business interests that important business problems and decisions can best be solved by methods covered in this course. The emphasis is placed on developing logical and systematic approaches in problem formulation and solution. Participation may include homework assignments, case studies, computer assignments, and periodic exams.


Goals and Objectives of the Course

At the conclusion of this course, student will be able to:
    1) Recognize and define business problems in a quantitative manner.
    2) Create quantitative models and apply best methods to facilitate decision making.
    3) Relate the fundamental logic behind statistical and quantitative methods to identify problems and lead further analysis.
    4) Employ advanced MS Excel skills for statistical and quantitative analysis.
    5) Interpret and report analysis results for various audiences.
    6) Present business problems and analysis results with visualization techniques to convey fast insight to audiences.
    7) Convince audiences with statistical and quantitative results with oral communication
    8) Lead decision making with the analysis results and implement the decision.


Assessment Measures

Graded assignments may include solution and reporting of case analyses by students, in-class tests, a final examination, pop quizzes, homework and computer assignments as well as class participation.


Other Course Information


The instructor may use computer software, videotapes, and the Internet to illustrate specific concepts and to promote class discussion.

 

Review and Approval

March 1, 2018

April 18, 2016

March 2013

April 2009

October 2004

March 01, 2021