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Quadratic Functions
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Quadratic Functions
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Now ยท ๐ฏ Learning Objectives
Quadratic Functions
๐ฏ Learning Objectives
By the end of this topic, you will be able to:
- Identify a quadratic function from its standard form f(x)=ax2+bx+c
- Find the vertex, axis of symmetry, and intercepts of a parabola
- Determine whether the parabola opens upward or downward
- Sketch the graph of a quadratic function
- Find the maximum or minimum value of a quadratic function
- Compute the slope of a quadratic function at a point
๐ Prerequisites
- Straight Lines โ slope, intercepts, linear equations
- Functions โ domain, range, function notation
- Algebra โ completing the square, solving linear equations
๐ Core Content
3.1 Intuition: The Shape of a Ball in Flight
Throw a ball into the air. It rises, slows, reaches a peak, then falls back down. If you plot its height over time, you get a smooth U-shaped curve called a parabola. This is the graph of a quadratic function.
Quadratic functions model:
- Projectile motion (height vs. time)
- Profit optimization (revenue vs. price)
- Area problems (maximizing space with fixed perimeter)
- The shape of satellite dishes and headlight reflectors
๐ก Why this matters: Quadratics are the simplest non-linear functions. Understanding them is the first step toward understanding all higher-degree polynomials and the curvature of functions โ essential for optimization in machine learning (gradient descent finds minima of functions).
3.2 Formal Definition
A quadratic function is any function that can be written in the form:
where a, b, c are real constants and a๎ =0 (if a=0, it's linear).
| Component | Name | Role |
|---|---|---|
| a | Leading coefficient | Determines "width" and direction (up/down) of parabola |
| b | Linear coefficient | Affects position of vertex horizontally |
| c | Constant term | y -intercept: f(0)=c |
| ax2 | Quadratic term | Gives the U-shape |
(Diagram)
3.3 Key Features of a Parabola
3.3.1 Vertex
The vertex is the turning point of the parabola โ where it changes from increasing to decreasing (or vice versa). It is the minimum (if a>0) or maximum (if a<0).
Derivation (completing the square):
f(x) &= ax^2 + bx + c \\[2pt] &= a\left(x^2 + \frac{b}{a}x\right) + c \\[2pt] &= a\left[\left(x + \frac{b}{2a}\right)^2 - \frac{b^2}{4a^2}\right] + c \\[2pt] &= a\left(x + \frac{b}{2a}\right)^2 + \left(c - \frac{b^2}{4a}\right) \end{aligned}
\boxed{(-3, -4)}
\boxed{\text{Maximum } 5 \text{ at } x = 2}
\boxed{x = 2}
\boxed{f(x) = (x - 5)^2 + 3}
\boxed{(0, 4)}
\boxed{25 \text{ units gives profit } \$425}
\boxed{-12,\ 0,\ 12}
\boxed{\text{Reflect + stretch, left 3, up 5}}
\boxed{10\text{m} \times 10\text{m} \text{ (a square)}}
\boxed{0 \text{ (no real intercepts)}}
\boxed{f(x) = 3x^2 - 12x + 16}
\boxed{b = -6,\ c = 8}$$ --- ## ๐ Cross-References - Next topic: [Quadratic Equations & Discriminant](quadratics-equations.md) - Related: [Polynomials](../week04/polynomial-operations.md) โ quadratics are degree-2 polynomials - Across courses: BSMA1002 Stats 1 (quadratic regression); BSMA1003 Maths 2 (conic sections); gradient descent in ML optimizes quadratic-like loss functions
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