Unit 13 · Lesson 02 · Open-Age
Select Variables, Functions, Data & Assumptions
Model design translates a real situation into mathematics. Assumptions should be explicit and testable, and the chosen function family should match observed structure.
Learning objectives
- Explain the central structure of select variables, functions, data & assumptions using precise mathematical language.
- Apply the governing relationship and verify results with an alternate representation or substitution.
- State domain, unit, precision, and context restrictions whenever they affect the result.
- Analyze a misconception and communicate a correction with evidence.
Essential question: How can a transparent, tested, and ethically communicated mathematical model support a real decision?
Governing relationship
Define variables, units, assumptions, data, and candidate model families.
Model design translates a real situation into mathematics. Assumptions should be explicit and testable, and the chosen function family should match observed structure.
Worked examples
Read each example, close it, and reconstruct the reasoning independently. Then verify by substitution, graph, table, or alternate method.
Guided and independent practice
- Define dependent and independent variables.
- Choose candidate functions.
- Document assumptions and data provenance.
- Create one original example involving select variables, functions, data & assumptions and solve it completely.
- Use the Khaemenes Scientific Calculator to verify one result, then document the setup and reasonableness check.
- Write a one-paragraph explanation connecting symbolic, graphical, numerical, and contextual representations.
Differentiated pathways
Foundation
Review prerequisite vocabulary, annotate each worked step, complete the first four prompts, and use a table or graph to support symbolic work.
Core
Complete every prompt, explain domain and verification, correct errors, and submit the applied task with clear mathematical communication.
Extended
Generalize the relationship, compare methods, use technology strategically, analyze sensitivity, and create a proof, counterexample, or advanced model.
Application laboratory
Write a model plan with variables, units, assumptions, tools, and validation criteria.
Required evidence: defined quantities and units; at least two representations; transparent calculations; verification; one limitation; and a defensible conclusion.
Misconception and correction
Common misconception: Selecting a model before inspecting structure or data.
Write the first invalid step, the governing rule that corrects it, and one counterexample or verification that demonstrates the correction.
Mastery evidence
- Accurate symbolic work with preserved equivalence.
- Correct domain, interval, unit, and precision statements.
- At least one independent verification.
- A correction explaining why an incorrect approach fails.
- A clear application conclusion that distinguishes mathematical result from recommendation.
Reflection
What structure did you recognize? Which representation was most useful? What assumption or restriction mattered most? What will you do differently on the next problem?