Gradients and the Power Rule
What the gradient of a curve means, how chords close in on the tangent, and the power rule that makes differentiating fast, including roots, fractions and second derivatives.
Learning objectives
- Explain the gradient of a curve at a point as the limit of the gradients of chords.
- Differentiate for any rational , and sums and differences of such terms.
- Rewrite roots, fractions and products as powers of before differentiating.
- Find gradients at points, points with a given gradient, and second derivatives.
A straight line has the same gradient everywhere. The curve gets steeper as increases. How could you measure "how steep" it is at exactly ?
Core idea
A car's distance from home is metres after seconds. Its average speed over the first seconds is m/s. But what does the speedometer read at the exact instant ? Speed is distance ÷ time, and at an instant no time passes: . For 2000 years that looked impossible. Newton and Leibniz cracked it by taking smaller and smaller time intervals and seeing what the average speed approaches. That idea is the derivative.
The derivative is the gradient of a curve at a point: the limit of chord gradients as the chord shrinks. For powers of , .
1. The problem: a curve has no single gradient
A straight line has the same steepness everywhere. A curve like gets steeper as you move right. "The gradient at a point" means the gradient of the tangent there: the straight line that just touches the curve at that point and runs in the same direction.
2. Chords closing in on the tangent
- is a nearby point, to the right ().
- Chord gradient: rise over run.
- Expand .
- Simplify; divide by (allowed since ).
- As slides to , shrinks to .
Do the same at a general point to get a formula for the gradient everywhere. This is called differentiation from first principles.
- where
- a small step in .
- "the value approached as gets closer and closer to ".
- ,
- two notations for the derivative (gradient function).
- Chord gradient from to .
- Expand (binomial).
- Cancel ; divide by .
- Terms with vanish.
3. The power rule
, ; in general (using the binomial expansion of , whose second term is ):
- where
- any real power: positive, negative or fractional.
- a constant; its graph is flat, so gradient 0.
Differentiate a sum term by term. Before differentiating, rewrite roots and fractions as powers: , .
Find .
- Goal
- The gradient function.
- Strategy
- Rewrite every term as a power of , then apply the power rule to each.
- Rewrite.
- Bring the power down; reduce it by one.
- Tidy.
For : find the gradient at , the points where the gradient is , and .
- Goal
- Three results.
- Strategy
- Differentiate; substitute or solve.
- Power rule.
- Substitute.
- Set equal and solve.
- Differentiate again: the second derivative, the rate of change of the gradient.
Find for .
Summary
- Derivative = limit of chord gradients.
- ; constants vanish.
- Rewrite as powers first.
- : differentiate twice.
- Derivative
- Gradient function.
- Tangent
- Line touching a curve, with its gradient.
- Limit
- The value approached.
- First principles
- Deriving the gradient from chords.
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