BZAN 6310

Quantitative Analysis for Business Decisions

Performance Analytics

Course Overview

BZAN 6310 introduces students to the core principles of business analytics and statistical reasoning, with a focus on applying quantitative methods to real-world business problems. The course emphasizes the use of technology tools and data-driven decision-making to support performance management, cost optimization, and financial analysis across business functions.

Students will develop fluency in descriptive, predictive, and prescriptive analytics, and learn to interpret data through the lens of Business Finance. This course serves as a critical foundation for advanced study in supply chain analytics, operations, and strategic business decision-making.

Course Purpose

The purpose of this course is to equip students with the analytical and statistical skills necessary to evaluate business performance, manage uncertainty, and support strategic decisions. Students will learn to apply quantitative techniques using Excel and other tools to analyze data from operations, finance, marketing, and supply chain contexts.

The course also emphasizes ethical data use, governance, and the importance of clear communication in translating analytical results into actionable business insights.

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Learning Objectives

By the end of this course, students will be able to:

  • Apply statistical methods to analyze business data and support decision-making under uncertainty.
  • Interpret and communicate the results of quantitative analysis in a business context.
  • Use Excel and other technology tools to perform descriptive, predictive, and prescriptive analytics.
  • Evaluate business performance using financial metrics and statements, including the Balance Sheet, Income Statement, and Statement of Cash Flows.
  • Identify and correct inappropriate assumptions, data manipulation, or misuse of statistical methods.
  • Support performance analytics and cost optimization initiatives through data-driven insights.
  • Understand the role of analytics in business governance, risk management, and strategic planning.

Topics Covered

  • Descriptive Statistics and Data Visualization
  • Relationships Among Variables and Correlation Analysis
  • Probability Theory and the Normal Distribution
  • Sampling, Confidence Intervals, and Hypothesis Testing
  • Regression Analysis and Statistical Inference
  • Predictive Modeling and Forecasting
  • Data Mining and Pattern Recognition
  • Optimization and Prescriptive Analytics
  • Financial Statement Interpretation and Business Metrics
  • Managerial Accounting and Cost Analysis
  • Ethics and Governance in Data Analytics

Experiential Learning & Course Pedagogy

The course uses a flipped classroom model, where students review lecture content online and use class time for hands-on problem solving, discussion, and collaborative exercises. Students engage in:

  • Case-based learning to apply statistical methods to real business scenarios.
  • Excel-based modeling to build and analyze data sets.
  • Interactive discussions on ethical considerations and governance in analytics.
  • A capstone case study that integrates statistical analysis with financial interpretation and business strategy.

This approach ensures students gain both the technical skills and the critical thinking required to succeed in data-intensive business environments.

Course Format & Assessment

The course is delivered in a hybrid format, combining asynchronous content with in-person sessions focused on application and discussion. Assessment includes:

  • Quizzes that progressively build analytical proficiency.
  • A comprehensive case study applying analytics to a business decision.
  • Three exams assessing conceptual understanding and applied skills.
  • Participation in class discussions and collaborative exercises.