Academic Catalog 2023-2024

Master of Science in Management Science and Quantitative Methods

Program Overview

Concordia's advanced degree in Management Science & Quantitative Methods (MSQM) provides professionals across industries and career levels with the skillsets needed to make strategic, data-driven decisions within their organizations. Throughout the program, students will explore analytical methods and tools to understand, interpret and apply data to complex, real-world problems, while honing leadership skills critical in today’s global business environment.

MSQM is ideal for busy, working professionals with a course schedule accommodating a work, life, and academic balance. An accelerated online format offering students a short break between courses. During fall semester, students select course options that align with their experience level and career goals. The program culminates with a professional capstone project focused on relevant business issues and challenges.


The requirements for a Master of Science in Management Science and Quantitative Methods are listed below.

Required Courses
DATA 600Data Analysis & Visualization3
BUSN 668Advanced Leadership3
DATA 665Advanced Operations Management/Research3
DATA 685Integrative Capstone Experience I3
DATA 686Integrative Capstone Experience II3
Elective Courses
Select a minimum of 20 credits from the following:20
Cost Accounting
Supply Chain & Risk Management
Leadership: Theory and Application
Statistics & Research Analysis
Data Mining
Corporate Finance
Operations Management/Research
Special Topics
Special Topics
Special Topics
Special Topics
Special Topics
Total Hours35


ACCT 626  -  Cost Accounting,  3 credits.  

This course focuses on the development and analysis of cost information used by management decision makers to evaluate and improve company performance. It includes product cost analysis, profitability planning, performance analysis and emerging cost strategies.

ACCT 680  -  Special Topics,  0-4 credits.  
Repeatable: Yes  
BUSN 610  -  Supply Chain & Risk Management,  3 credits.  

The main purpose of the course will be to learn about supply chain decisions. The students will be exposed to current topics in effectively managing supply chains, including supply chain design, strategies, integration, visualization, analytics, risk, and mitigation. The supply chain is constantly making changes and exposed to endogenous and exogenous risks, which cause interruptions to the flow of products and a significant impact on the performance of the business. Risks spread rapidly through the chain due to the interdependence of its various nodes. Thus understanding the supply chain risks can enable organizations to take effective action to identify, assess, and mitigate risks within their end-to-end supply chain.

BUSN 662  -  Leadership: Theory and Application,  3 credits.  

This course is designed to provide a comprehensive view of the nature and practice of leadership. Among the topics explored are historical, philosophical and theoretical foundations; ethics and values; power and influence; conflict management; and effective leadership in formal organizations.

BUSN 668  -  Advanced Leadership,  3 credits.  

This course explores advanced concepts and theories related to leadership with an emphasis on contemporary topics of leadership and factors that guide leader behavior. Students will examine classic and current scholarship to bridge theory and practice. The course focuses on critical thinking about leadership.

BUSN 680  -  Special Topics,  0-4 credits.  
Repeatable: Yes  
DATA 600  -  Data Analysis & Visualization,  3 credits.  

This course focuses on technical and visual aspects of inspecting and presenting data. Technical topics include importing data from various sources, establishing relationships between data tables, transforming data, filtering, sorting, and aggregation. Visuals will be designed to focus attention on what the data is saying, with a special focus on visuals that respond dynamically to user manipulations. Emphasis will be placed on the design/refinement cycle for visualizations.

DATA 608  -  Statistics & Research Analysis,  3-4 credits.  

This course allows the student to understand and demonstrate knowledge of descriptive and inferential statistics used in research, and apply their knowledge to real-world situations and research questions. Emphasis is placed on distinguishing similarities and differences among statistical tests, and recognizing the essentiality of statistics for producing and comprehending scientific research

DATA 617  -  Forecasting,  3 credits.  

Forecasting is the science of predicting future events and outcomes. In this course students will learn how to effectively use both data and theory to create forecasts and how to quantify and communicate uncertainty in forecasts. Topics include random walks, Markov models, time series analysis, Bayesian methods and qualitative forecasting.

Frequency: Alternate Years - 1st Semester  
DATA 618  -  Data Mining,  3 credits.  

Data mining is the study of discovering and assessing patterns, relationships and information within large data sets. This course provides an introduction to data mining with an emphasis on predictive modeling techniques and machine learning algorithms. Examples and applications will be drawn from various disciplines.

Prerequisites: DATA 608  
DATA 665  -  Advanced Operations Management/Research,  3 credits.  

Students will learn specialized applications of operations research to problems arising from business. These will include data envelope analysis, transportation/transshipment problems, goal programming, network models (including PERT-CPM), and capital budgeting. Other topics such as inventory models, facility location problems, etc. will be covered as time and student interest permit. Special attention will be paid to the development and analysis of models for realistic medium- to large-scale problems.

DATA 680  -  Special Topics,  0-4 credits.  
Repeatable: Yes  
DATA 685  -  Integrative Capstone Experience I,  3 credits.  

The main purpose of the capstone course is to provide the culminating, integrative curricular experience for students. The course consolidates students' learning to develop a project with knowledge gained from many areas in the MSQM. The focuses of the course are case analyses and professional development.

DATA 686  -  Integrative Capstone Experience II,  3 credits.  

Integrative Capstone Experience II's main purpose is to provide a structured means for students to get hands-on experience in real-life business analytics practices. Students will apply skills and knowledge gained throughout the MSQM program, such as statistical techniques, models, and analytical decision-making that support the business-defined problems scoped collaboratively between companies and Concordia.

Prerequisites: DATA 685 (may be taken concurrently)  
FIN 680  -  Special Topics,  0-4 credits.  
Repeatable: Yes  
MATH 635  -  Operations Management/Research,  3 credits.  

An introduction to the theory and practice of quantitative modeling and optimization, with applications to computer simulation and business resource management. Possible topics include linear and nonlinear programming, network analysis, game theory, deterministic and probabilistic models.

MATH 680  -  Special Topics,  0-4 credits.  
Repeatable: Yes