9D, 9E - Stationary and turning points
A horizontal tangent can mark the top of a hill, the bottom of a valley, or a place where a curve briefly flattens and carries on. You will find stationary points, justify their nature and distinguish a turning point from a stationary point without a turn.
Finding stationary points
If a curve has gradient zero, must it turn back? First we need to locate the points where this question arises.
For , the derivative is . It is zero at and . These are horizontal-tangent positions, but a position on the curve needs both coordinates.
Stationary point
A stationary point is a point on a curve where the derivative exists and is zero. For , solve , then substitute each solution into to find its -coordinate.
Do not solve : that finds crossings of the horizontal axis. Also check that each candidate belongs to the domain of the original function. A value excluded by a denominator cannot become a point on the curve.
Worked example 1: finding both coordinates
Question. Find the stationary points of .
Plan. Differentiate, solve the zero-gradient equation and recover the heights from the original equation.
At , . At , .
Answer. and .
Check. Both values give ; substituting both coordinate pairs into the original curve also works. The point shows why stationary points need not lie on the horizontal axis.
Now change only the coefficient of the linear term. The zero-gradient positions move, so the heights must be calculated again.
Worked example 2: changing the linear term
Question. Find the stationary points of .
Plan. Use the same zero-gradient method with the new derivative.
Substitution into the curve gives
Answer. and .
Check. The derivative at both positions is . Also is odd, so the two heights should be equally far above and below : they are and .
Use the derivative for positions and the original function for heights.
Classifying stationary points
A turning point is identified by what the gradient does on the two sides of it, rather than by its height above the axis.
At a local maximum, nearby curve values are no greater: the curve changes from increasing to decreasing. At a local minimum, nearby values are no smaller: the curve changes from decreasing to increasing. “Local” compares nearby points; it does not promise the greatest or least value on an entire domain.
Tests for a stationary point
At a stationary point with :
| Gradient just before | Gradient just after | Nature |
|---|---|---|
| positive | negative | local maximum |
| negative | positive | local minimum |
| same sign | same sign | no turn |
The second derivative, , is the derivative of . For the smooth functions here, establishes a local minimum and establishes a local maximum. If , this test is inconclusive; examine the first-derivative signs.
The second derivative measures how the gradient is changing. A positive value at a stationary point means the gradient is increasing through zero; a negative value means it is decreasing through zero.
Worked example 3: a maximum and a minimum
Question. Classify the stationary points and of .
Plan. Evaluate the second derivative at each stationary position.
At , , so is a local maximum. At , , so is a local minimum.
Answer. Local maximum at ; local minimum at .
Check. The factorisation gives signs on the intervals separated by and . These are precisely the required changes.
Reflect the curve in the horizontal axis by multiplying its function by . The stationary positions stay fixed, but the turns reverse.
Continue this lesson.
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