Maricopa Community Colleges  GBS220   19966-20065 

Official Course Description: MCCCD Approval: 06/25/96

GBS220 1996 Fall - 2006 Summer II

LEC  3.0 Credit(s)  3.0 Period(s)  3.0 Load  Acad

Quantitative Methods in Business

Business applications of quantitative optimization methods in operations management decisions.

Prerequisites: (Grade of "C" or better in MAT150, or MAT151, or MAT152) or equivalent, or satisfactory score on district placement exam.


Course Attribute(s):

General Education Designation: Mathematics - [MA]

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MCCCD Official Course Competencies:


GBS220 1996 Fall - 2006 Summer II

Quantitative Methods in Business



Identify business applications and problem situations where quantitative methods and modeling are useful for decision making. (I)


Model and solve a two-decision variable linear programming problem graphically, and interpret the answer. (II)


Model, solve, and interpret a linear programming problems using computer software. (II)


Compute probabilities using rules of multiplication and addition. (III)


Solve counting problems using permutations and combinations. (III)


Solve problems using discrete and continuous probability distributions. (IV)


Model, solve, and interpret Program Evaluation and Review Technique (PERT) and Critical Path Method (CPM) type problems. (V)


Model, solve, and interpret a decision problem involving uncertainty, using decision theory techniques. (VI)


Develop total cost and Economic Order Quantity (EOQ) models for specific inventory systems. (VII)

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MCCCD Official Course Outline:


GBS220 1996 Fall - 2006 Summer II

Quantitative Methods in Business


I. Importance of Quantitative Methods in Business

II. Linear Programming

A. Graphical solution

B. Computer solution

1. General optimization problems

2. Transportation problems

3. Assignment problems

III. Probability and Counting Methods

A. Rules of multiplication and addition

B. Bayes theorem

C. Combinations and permutations

IV. Probability Distributions

A. Random variables

B. Discrete random variables

C. The binomial distribution

D. Poisson distribution

E. The normal probability distribution


A. Networks

B. Critical path

C. Probability of completion

VI. Decision Theory

A. Maxi-min

B. Maxi-max

C. Mini-max regret

D. Probabilities

VII. Inventories

A. Total cost model

B. EOQ model


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