Introduction to Modelling with Standard Functions
In the real world, things rarely happen in a perfectly straight line. To understand the world around us—from how a virus spreads to how a ball flies through the air—we use mathematical models. A model is simply using a function to represent a real-life situation. In this chapter, we will explore the "menu" of standard functions available to you in the IB Applications and Interpretation course. Think of these as different tools in a toolkit; your job is to learn which tool fits which job!
Note: For help with drawing these on your calculator or finding where they cross, check out the chapters on "Graphs, key features and intersections" and "Modelling skills".
1. Linear Models: \(y = mx + c\)
The simplest model is the linear model. We use this when something changes by a constant amount for every unit of time or distance.
The Equation: \(f(x) = mx + c\)
- \(m\) (The Gradient): The rate of change. For every 1 unit \(x\) increases, \(y\) changes by \(m\).
- \(c\) (The y-intercept): The starting value when \(x = 0\).
Real-world example: A taxi ride that costs a fixed booking fee of \$5 plus \$2 per kilometer. The model would be \(C(x) = 2x + 5\).
2. Quadratic Models: \(y = ax^2 + bx + c\)
Quadratic models create a "U" shape (a parabola). They are perfect for situations that have a maximum or a minimum point.
The Equation: \(f(x) = ax^2 + bx + c\)
Key Features to Know:
- The Vertex: The highest or lowest point of the curve.
- Axis of Symmetry: The vertical line that cuts the parabola in half. It is always at \(x = -\frac{b}{2a}\).
- Zeros/Roots: Where the graph hits the x-axis (where \(y = 0\)).
- y-intercept: The value of \(c\).
Real-world example: Projectile motion. If you kick a football, it goes up, reaches a peak (the vertex), and comes back down. Its height over time is a quadratic model.
3. Exponential Models: Growth and Decay
Exponential functions are used when something changes by a percentage or a ratio rather than a flat amount. These functions grow or shrink very quickly!
The Equations:
1. \(f(x) = k a^x + c\)
2. \(f(x) = k a^{-x} + c\)
3. \(f(x) = k e^{rx} + c\)
Key Features:
- Horizontal Asymptote: This is the line \(y = c\). The graph will get closer and closer to this value but will never actually touch it. It represents a "floor" or "ceiling" for the model.
- Growth vs. Decay: If the base is greater than 1 (or the exponent is positive), it's growth. If the base is between 0 and 1 (or the exponent is negative), it's decay.
Real-world example: Compound interest in a bank account (growth) or the cooling of a cup of coffee toward room temperature (decay). The room temperature would be the horizontal asymptote \(c\).
4. Power Models: Direct and Inverse Variation
These models describe how one variable changes in proportion to another raised to a specific power.
The Equation: \(f(x) = a x^n\)
- Direct Variation (\(n > 0\)): As \(x\) goes up, \(y\) goes up. For example, the area of a square \(A = s^2\).
- Inverse Variation (\(n < 0\)): As \(x\) goes up, \(y\) goes down. A common form is \(y = \frac{a}{x}\) (where \(n = -1\)).
- Vertical Asymptote: When \(n\) is negative (inverse variation), the y-axis (\(x = 0\)) becomes a vertical asymptote because you cannot divide by zero!
Quick Tip: If you see a graph that looks like it's "hugging" the y-axis and the x-axis, it's likely an inverse variation model.
5. Cubic Models: \(y = ax^3 + bx^2 + cx + d\)
Cubic models can have two "turns" (a local maximum and a local minimum). They are useful for more complex data that changes direction twice.
Real-world example: The volume of a shape where all dimensions are changing, or certain complex cost functions in economics.
6. Sinusoidal Models: Periodic Waves
Sinusoidal models are used for periodic behavior—things that repeat in a regular cycle over time.
The Equations:
\(f(x) = a \sin(bx) + d\)
\(f(x) = a \cos(bx) + d\)
Key Features:
- \(a\) (Amplitude): The height from the middle of the wave to the top. It shows how far the values "stretch" from the center.
- \(d\) (The Principal Axis / Midline): The average value. The wave oscillates above and below this line \(y = d\).
- \(b\): This affects the period (how long it takes for one full cycle to complete).
Real-world example: The rising and falling of tides, the height of a person on a Ferris wheel, or seasonal temperature changes.
Did you know? Your heart rate on an EKG monitor is a real-life version of a periodic (sinusoidal-style) function!
Summary Table for Quick Review
Linear: Constant rate of change. Constant slope.
Quadratic: Has a "turning point" (Vertex). Symmetric.
Exponential: Rapid change. Has a horizontal asymptote.
Inverse: One value increases as the other decreases. Hugs the axes.
Sinusoidal: Repetitive, wave-like motion.
Common Mistakes to Avoid
- Confusing \(x^2\) and \(2^x\): Remember, if the \(x\) is the "base" (bottom), it's Quadratic. If the \(x\) is the "exponent" (top), it's Exponential.
- Forgetting the Asymptote: When sketching exponential or inverse functions, always draw the dotted line for the asymptote and label it.
- Calculator Radians: For Sinusoidal models, always check if your GDC (calculator) is in Radians or Degrees. Usually, IB modelling questions use Radians unless degrees are specified!
Key Takeaway: Choosing a model is about looking at the shape of the data. Does it go up forever (Linear/Exponential)? Does it turn back (Quadratic)? Does it repeat (Sinusoidal)? Once you identify the shape, you've found your model!