The Math for Liberal Arts textbook contains twelve modules—roughly one module per week for a 12-week semester.

If you plan to modify the pace of the course or rearrange the order of the modules, please keep the following notes in mind to ensure your students are well prepared for new concepts:

• Module 1: Historical Counting Systems can be skipped without affecting future modules.
• Module 2: General Problem Solving should be taught either first or second.
• Module 3: Measurement is best taught immediately after Module 2: General Problem Solving.
• Module 4: Graph Theory can be skipped without affecting future modules.
• Module 5: Fractals can be skipped without affecting future modules.
• Module 7: Voting Theory can be skipped without affecting future modules.
• Module 8: Growth Models should be taught before Module 9: Finance.
• Module 10: Statistics – Collecting Data should be taught before Module 11: Statistics – Describing Data.
• Module 12: Probability should be taught after Module 10: Statistics – Collecting Data and Module 11: Statistics – Describing Data.

A few additional notes involving possible adjustments:

• Module 3: Measurement can be combined with Module 5: Fractals, completed together in a week’s time.
• If you want to go into more depth with fractal dimension, teach Module 5: Fractals after Module 8: Growth Models and Module 9: Finance, where logarithms are introduced and practiced in applications. Computations of fractal dimension in Module 5: Fractals are presented as a calculator exercise, and therefore do not require knowledge of properties of logarithms.
• Module 7: Voting Theory can be taught any time after Module 2: General Problem Solving. Computation in this module is minimal, where the focus is on the use of logic and following a set of prescribed practices for tallying ballots.

We recommend NOT doubling up the following modules, as they are more dense than other modules, or provide important foundational concepts:

• Module 2: General Problem Solving: foundational
• Module 4: Graph Theory: dense
• Module 6: Set Theory and Logic: dense
• Module 12: Probability: dense