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NotesMath AI SLTopic 2.5Power and variation models
Back to Math AI SL Topics
2.5.41 min read

Power and variation models

IB Mathematics: Applications and Interpretation • Unit 2

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Contents

  • What is a power model?
  • Power vs exponential — the key difference
  • Using GDC for power regression
  • Interpreting and validating a power model
Power model: y = axⁿ: A power model describes situations where one quantity is proportional to a power of another. The exponent n determines the shape. Unlike exponential models (where x is in the exponent), in a power model x is the base.
Scaling constant (positive for real-world models)
Exponent — can be any real number (2, 3, 0.5, −1, etc.)
Independent variable (the base)
n valueShapeReal-world example
n = 2Parabola (upward)Area of circle: A = πr²
n = 3CubicMass ∝ (height)³ for animals (Rubner's law)
n = 0.5Square root curveSpeed of waves on water
n = −1Hyperbola (inverse proportion)Smoothie sales: n = 40000/x² (n = −2)
n = −2Steeper hyperbolaIntensity ∝ 1/distance²
Power model vs exponential model — easy to confuse: These two look similar but are fundamentally different. In a power model the variable x is the BASE. In an exponential model x is the EXPONENT.
Model typeFormx is...Example
Powery = axnthe BASEMass = 125 × h³ (h = height)
Exponentialy = a × bxthe EXPONENTPopulation = 200 × 1.15t

Big cats: mass m (kg) is proportional to (height h)³. A cheetah has m = 64 kg at h = 0.8 m. (a) Find the constant of proportionality. (b) Find m when h = 0.75 m.

Step by step

  1. Write the power model.
  2. Substitute known values to find a.
  3. Write the complete model.
  4. Substitute h = 0.75.

Final answer

The constant is a = 125. A cheetah of height 0.75 m has mass ≈ 52.7 kg.

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GDC PwrReg finds the best-fit power model: When given a table of data that follows a power relationship, use the GDC's Power Regression (PwrReg) to find the values of a and n that best fit the data.

GDC steps for power regression (TI-84)

  • Enter x-values in L1, y-values in L2.
  • Press STAT → CALC → A:PwrReg.
  • Confirm L1, L2. Press ENTER.
  • Read off a and b (the GDC uses "b" for the exponent).
  • Store to Y1 using RegEQ if you want to graph and evaluate.

A shop models smoothie sales as n = axb where x is price (pesos). Data gives PwrReg: a = 40000, b = −2. Find the maximum number of smoothies sold per day if each smoothie costs 50 pesos.

Step by step

  1. Write the model from GDC output.
  2. Substitute x = 50.

Final answer

At a price of 50 pesos, the shop sells 16 smoothies per day.

Check: does the model make physical sense?: After finding a power model, always verify it gives sensible values at the extremes. If the model predicts a negative mass or infinite sales, something is wrong with the domain.

✗ Common mistakes

  • Confusing a power model y = axn with y = ax (exponential)
  • Forgetting units — "m = 52.7" means nothing without "kg"
  • Not checking whether the GDC a and n match the physical story

✓ Correct approach

  • Check: is x the base (power) or the exponent (exponential)?
  • Always attach units to every answer: m ≈ 52.7 kg
  • Verify with one known data point: does 125(0.8)³ = 64? Yes ✓
Direct vs inverse proportion: n > 0: as x increases, y increases (direct power proportion). n < 0: as x increases, y decreases (inverse power proportion). State this in your interpretation: "As height increases, mass increases (direct proportion to h³)."

IB Exam Questions on Power and variation models

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How Power and variation models Appears in IB Exams

Examiners use specific command terms when asking about this topic. Here's what to expect:

Define

Give the precise meaning of key terms related to Power and variation models.

AO1
Describe

Give a detailed account of processes or features in Power and variation models.

AO2
Explain

Give reasons WHY — cause and effect within Power and variation models.

AO3
Evaluate

Weigh strengths AND limitations of approaches in Power and variation models.

AO3
Discuss

Present arguments FOR and AGAINST with a balanced conclusion.

AO3

See the full IB Command Terms guide →

Related Math AI SL Topics

Continue learning with these related topics from the same unit:

2.1.1Gradient and y-intercept
2.1.2Writing the equation of a straight line
2.1.3Parallel and perpendicular lines
2.1.4Linear models in context
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Sinusoidal models2.5.5

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