Course Description

MA 114 introduces mathematical modeling techniques commonly used in behavioral, management, and biological sciences. Topics emphasize translating real-world problems into quantitative models using finite mathematics tools and interpreting results critically.

Topics Covered

• Elementary matrix algebra and solving linear systems
• Matrix inverses and input-output models
• Linear programming and the simplex method
• Sets, permutations, combinations, and probability
• Conditional probability and Bayes’ Theorem
• Markov chains and steady-state modeling

Learning Outcomes

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

• Solve applied linear systems using matrix methods
• Formulate and solve optimization problems via simplex method
• Apply combinatorics to model probability events
• Analyze probabilistic behavior using Markov models
• Interpret the long-term behavior of discrete dynamical systems

Textbooks & Resources

1. Waner & Costenoble
   Finite Mathematics, 6th ed. — delivered via WebAssign
   Also accessible through NC State Libraries.

2. Recommended Tools

   • ZweigMedia Finite Math Toolkit — interactive matrix solvers, simplex animations, probability demos
   • Applied Finite Mathematics (Open Textbook) — full, free textbook aligned with MA 114 topics
   • Desmos Graphing Calculator — for inequality visualization and LP regions
   • NC State Moodle — access to WebAssign, grades, and announcements

Grading Breakdown

• WebAssign Homework — 20%
• Three Proctored Tests — 60% (20% each)
• Comprehensive Final Exam — 20%

Tips for Self-Guided Learning

• Use ZweigMedia to practice matrix algebra and linear programming with visual feedback
• Explore Open Textbook examples for clear walkthroughs of counting and probability
• Build LP intuition by visualizing constraint regions in Desmos
• Follow WebAssign deadlines closely and review test feedback on Moodle

This page summarizes the Spring 2024 version of MA 114. Policies and tools may evolve in future semesters.