Math 106 Introduction to Mathematical Modeling

Oct 24, 2025 · 2 min read

Course Description

This is a Quantitative Reasoning keystone course meant for non-science majors. The course is intended to provide insight into the importance of mathematics to the world outside academia, and to improve students reasoning and problem—solving skills. It will introduce to students applications by way of management decision making, social choice, and population studies. Typical among problems to be studied are: scheduling of projects with precedence restrictions; linear Programming problems; manipulability of voting systems; weighted voting systems (coalitions and relative power, paradoxes in voting systems); apportionment; fair division in presence of individual preferences; detection and or correction of data transmission errors.

🗂 Lecture Notes

📅 Weekly Materials

Find all weekly lecture notes below.

📘 Weekly lecture Notes

🕓 Week 📘 Lecture Notes
1 Lecture 1, Lecture 2
2 Lecture 3, Lecture 4
3 Lecture 5, Lecture 6
4 Lecture 7, Lecture 8
5 Lecture 9, Lecture 10
6 Lecture 11, Lecture 12
6 Lecture 13, Lecture 14

🧮 Homework

🗓 Weekly Homework Assignments

Each week’s homework corresponds to the lecture topics covered. Downloadable PDFs are provided below.

🕓 Week 🧾 Homework 📅 Due Date
1 Homework 1 Sep 17
2 Homework 2 Sep 29
3 Homework 3 Oct 6
4 Homework 4 Oct 27
5 Homework 5 Nov 3
6 Homework 6

💡 Homework Notes & Solutions

📘 Week 🧩 Solutions / Notes
1 Homework 1 Solutions
2 Homework 2 Solutions
3 Homework 3 Solutions
4 Homework 4 Solutions
5 Homework 5 Solutions
6 Homework 6 Solutions

🧭 Notes on Submission

  • Submit all homework via Canvas or in-person by the due date listed.
  • Late submissions accepted up to 48 hours with a 10% penalty.
  • Show all work and clearly label answers.

Course Syllabus

Download the MATH 106 Course Syllabus (PDF)

Instructor Information

  • Instructor: Dr. Atul Anurag
  • Email: aanurag@ramapo.edu
  • Office Hours:
    • In-person or virtual, by appointment
    • Mondays and Thursdays: 12:00 PM to 1:00 PM
    • Other days/times: By appointment
  • Location: G128H