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
- Identify model type from context or graph shape
- Use GDC regression to find parameters from data
- Check reasonableness of model predictions
- State domain restrictions for real-world context
- Interpret parameters in context (what does A represent?)
- Verify predictions make sense practically
- For optimization: Find max/min using calculus or GDC
🚫 Top Mistakes to Avoid
- Choosing wrong model type for the situation
- Not checking domain restrictions (e.g., time can't be negative)
- Extrapolating too far beyond data range
- Forgetting units in final answer
- Not interpreting parameters in context
- Mixing up amplitude and midline in sinusoidal functions
- Using exponential when logistic is more appropriate
- For piecewise: using wrong piece of function