IB Mathematics AI – Topic 2

Functions: Applications & Modeling

Linear Models

Definition & Applications

Definition: A linear model represents a relationship where the rate of change is constant. Used when one quantity changes at a steady rate with respect to another.

General Form:

\[ y = mx + c \]

Common Applications:

  • Cost functions: Total cost = fixed cost + (variable cost × quantity)
  • Distance-time: Distance = speed × time (constant speed)
  • Temperature conversion: F = 1.8C + 32
  • Depreciation: Straight-line depreciation

⚠️ Tips:

  • m represents rate of change per unit
  • c is the initial value (when x = 0)
  • Linear models work best for short-term predictions

Quadratic Models

Parabolic Relationships

General Forms:

Standard form:

\[ y = ax^2 + bx + c \]

Vertex form:

\[ y = a(x - h)^2 + k \]

where (h, k) is the vertex

Key Features:

  • Vertex: Maximum or minimum point
  • Axis of symmetry: \(x = -\frac{b}{2a}\)
  • Direction: Opens up if a > 0, down if a < 0

Applications:

  • Projectile motion: Height vs. time
  • Area optimization: Maximum enclosed area
  • Profit maximization: Revenue - Cost
  • Satellite dishes: Parabolic reflectors

⚠️ Tips:

  • Use vertex form when you know maximum/minimum
  • Use GDC to find vertex and roots
  • Check domain restrictions for real-world problems

📝 Worked Example 1: Projectile Motion

Question: A ball is thrown upward. Its height h (in meters) after t seconds is given by \(h(t) = -5t^2 + 20t + 2\).

(a) Find the maximum height reached.

(b) When does the ball hit the ground?

Solution:

(a) Maximum height:

Maximum occurs at vertex. Time at vertex:

\[ t = -\frac{b}{2a} = -\frac{20}{2(-5)} = -\frac{20}{-10} = 2 \text{ seconds} \]

Maximum height:

\[ h(2) = -5(2)^2 + 20(2) + 2 = -20 + 40 + 2 = 22 \text{ meters} \]

(b) When ball hits ground (h = 0):

Solve: \(-5t^2 + 20t + 2 = 0\)

Using quadratic formula or GDC:

\[ t = \frac{-20 \pm \sqrt{20^2 - 4(-5)(2)}}{2(-5)} = \frac{-20 \pm \sqrt{440}}{-10} \]

\[ t \approx 4.10 \text{ seconds (taking positive value)} \]

Answers: (a) 22 meters, (b) 4.10 seconds

Direct and Inverse Variation

Proportional Relationships

Direct Variation:

y varies directly as x (or y is directly proportional to x)

\[ y = kx \quad \text{or} \quad y \propto x \]

where k is the constant of proportionality

Properties: When x doubles, y doubles; when x = 0, y = 0

Inverse Variation:

y varies inversely as x (or y is inversely proportional to x)

\[ y = \frac{k}{x} \quad \text{or} \quad y \propto \frac{1}{x} \]

Properties: When x doubles, y halves; xy = k (constant)

Applications:

  • Direct: Distance = speed × time (constant speed)
  • Direct: Hooke's Law: Force ∝ extension
  • Inverse: Speed = distance/time (constant distance)
  • Inverse: Boyle's Law: Pressure ∝ 1/volume

⚠️ Tips:

  • Direct variation: straight line through origin
  • Inverse variation: hyperbola, never touches axes
  • Always find k first using given values

Exponential Models

Growth and Decay

General Form:

\[ y = Ab^x \quad \text{or} \quad y = Ae^{kx} \]

where A is initial value, b is base (or e with rate k)

Growth (b > 1 or k > 0):

  • Population growth: \(P(t) = P_0e^{rt}\)
  • Compound interest: \(A = P(1+r)^t\)
  • Bacterial growth

Decay (0 < b < 1 or k < 0):

  • Radioactive decay: \(N(t) = N_0e^{-\lambda t}\)
  • Drug concentration in body
  • Temperature cooling (Newton's Law)

Half-life and Doubling Time:

Half-life: Time for quantity to reduce to half

\[ t_{1/2} = \frac{\ln 2}{k} \]

Doubling time: Time for quantity to double

\[ t_d = \frac{\ln 2}{r} \]

⚠️ Tips:

  • Exponential growth increases rapidly
  • Use natural log (ln) to solve for time
  • Check if model uses e or another base

Logarithmic Models

Inverse of Exponential

General Form:

\[ y = a + b\ln(x) \quad \text{or} \quad y = a + b\log(x) \]

Properties:

  • Grows slowly (slower than linear for large x)
  • Only defined for x > 0
  • Has vertical asymptote at x = 0

Applications:

  • pH scale: Acidity measurement
  • Richter scale: Earthquake magnitude
  • Decibels: Sound intensity
  • Learning curves: Skill acquisition

Sinusoidal Models

Periodic Functions

General Form:

\[ y = A\sin(B(x - C)) + D \quad \text{or} \quad y = A\cos(B(x - C)) + D \]

Parameters:

  • A: Amplitude (half the distance between max and min)
  • B: Affects period: \(P = \frac{2\pi}{B}\)
  • C: Horizontal shift (phase shift)
  • D: Vertical shift (midline)

Applications:

  • Tides: Sea level vs. time
  • Temperature: Daily/seasonal variation
  • Sound waves: Oscillations
  • Ferris wheel: Height vs. time
  • Daylight hours: Throughout the year

⚠️ Tips:

  • Amplitude = (max - min)/2
  • Midline D = (max + min)/2
  • Use GDC regression for sinusoidal fitting

📝 Worked Example 2: Temperature Model

Question: Temperature in a city varies sinusoidally. Maximum is 28°C at 2pm, minimum is 12°C at 2am. Find model \(T(t)\) where t is hours after midnight.

Solution:

Step 1: Find amplitude A

\[ A = \frac{\text{max} - \text{min}}{2} = \frac{28 - 12}{2} = 8 \]

Step 2: Find midline D

\[ D = \frac{\text{max} + \text{min}}{2} = \frac{28 + 12}{2} = 20 \]

Step 3: Find period and B

Period = 24 hours (daily cycle)

\[ B = \frac{2\pi}{24} = \frac{\pi}{12} \]

Step 4: Find phase shift C

Maximum at t = 14 (2pm), so use cosine:

\[ T(t) = 8\cos\left(\frac{\pi}{12}(t - 14)\right) + 20 \]

Answer: \(T(t) = 8\cos\left(\frac{\pi}{12}(t - 14)\right) + 20\)

Logistic Models (HL)

Limited Growth

General Form:

\[ y = \frac{L}{1 + Ae^{-kx}} \]

where:

  • L: Carrying capacity (limiting value)
  • A: Constant determining initial value
  • k: Growth rate

Properties:

  • S-shaped curve (sigmoid)
  • Starts with exponential growth
  • Slows as it approaches carrying capacity L
  • Horizontal asymptote at y = L

Applications:

  • Population growth: Limited by resources
  • Disease spread: Limited by total population
  • Learning curves: Skill mastery plateaus
  • Technology adoption: Market saturation

⚠️ Tips:

  • More realistic than exponential for long-term growth
  • Use GDC for logistic regression
  • Carrying capacity is the maximum sustainable value

Piecewise Functions

Functions with Different Rules

Definition: A function defined by different formulas on different parts of its domain.

General Form:

\[ f(x) = \begin{cases} f_1(x) & \text{if } x < a \\ f_2(x) & \text{if } a \leq x < b \\ f_3(x) & \text{if } x \geq b \end{cases} \]

Applications:

  • Tax brackets: Different rates for income ranges
  • Shipping costs: Rates by weight/distance
  • Parking fees: First hour, additional hours
  • Utility bills: Tiered pricing

⚠️ Tips:

  • Check which piece applies for given x value
  • Pay attention to < vs ≤ at boundaries
  • Graph may have jumps (discontinuities)
  • Evaluate carefully at boundary points

📊 Function Models Quick Reference

When to Use Each Model

  • Linear: Constant rate of change
  • Quadratic: Has max/min point
  • Exponential: Rapid growth/decay
  • Sinusoidal: Periodic patterns

Key Characteristics

  • Direct: y = kx
  • Inverse: y = k/x
  • Logistic: S-curve with limit
  • Piecewise: Different rules

✍️ IB Exam Strategy

  1. Identify model type from context or graph shape
  2. Use GDC regression to find parameters from data
  3. Check reasonableness of model predictions
  4. State domain restrictions for real-world context
  5. Interpret parameters in context (what does A represent?)
  6. Verify predictions make sense practically
  7. For optimization: Find max/min using calculus or GDC

🚫 Top Mistakes to Avoid

  1. Choosing wrong model type for the situation
  2. Not checking domain restrictions (e.g., time can't be negative)
  3. Extrapolating too far beyond data range
  4. Forgetting units in final answer
  5. Not interpreting parameters in context
  6. Mixing up amplitude and midline in sinusoidal functions
  7. Using exponential when logistic is more appropriate
  8. For piecewise: using wrong piece of function