The Mean Value Theorem & Rolle's Theorem
If is continuous on the closed interval and differentiable on the open interval , then there exists at least one in with
That is, the instantaneous rate at some interior point equals the average rate of change over : some tangent line is parallel to the secant line.
If is continuous on , differentiable on , and , then there is a in with .
Let on . It is a polynomial, so continuous and differentiable everywhere. The average rate is
Set , so , which lies in . ✓
Let on . Then , and is a polynomial, so Rolle applies. Solving gives in . ✓
Tip: Always verify the hypotheses first. For on we have , but is not differentiable at , so Rolle's Theorem does not apply.
Increasing/Decreasing & the First Derivative Test
On an interval where , is increasing; where , is decreasing. First Derivative Test: at a critical number (where or is undefined):
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- changes at local maximum;
- changes at local minimum;
- no sign change neither.
, so critical numbers are .
Local max at with ; local min at with .
Tip: Critical numbers only name candidates. A sign change of is what confirms an extremum. Test one point in each interval.
Concavity, the Second Derivative Test & Inflection Points
Where , is concave up (); where , is concave down (). An inflection point is where concavity changes---so must change sign there. Second Derivative Test: if , then local min, local max, and is inconclusive.
. Then for (concave down) and for (concave up); the concavity changes at , so is an inflection point. Using the Second Derivative Test at the critical numbers: (local max) and (local min), matching the First Derivative Test.
For , , which is at but never changes sign (). So is not an inflection point--- is concave up throughout.
Tip: An inflection point requires an actual sign change of , not merely .
The Extreme Value Theorem & Absolute Extrema (Candidates' Test)
If is continuous on a closed interval , then attains an absolute maximum and an absolute minimum on . Candidates' Test: the absolute extrema occur at (i) critical numbers in or (ii) the endpoints. Evaluate at every candidate and compare.
(in the interval). Evaluate all candidates:
Absolute maximum at ; absolute minimum at .
Tip: On a closed interval you compare numbers, not signs. Never forget the endpoints---they are candidates too.
Optimization (Applied Max/Min)
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- Draw a picture; name variables.
- Write the quantity to optimize (the objective).
- Use a constraint to reduce to one variable; state the domain.
- Differentiate, find critical numbers, and justify the extremum (1st/2nd derivative test or endpoints).
Cut squares of side from each corner and fold. The volume is
Then . Setting : (gives ) or . Since changes at , it is a maximum:
Tip: Always state the domain from the physical situation, then justify that your critical number gives the max or min---do not just assert it.
Curve Sketching & Connecting , ,
Combining the work above: increasing on and , decreasing on ; local max , local min ; concave down for , up for ; inflection .
For we get and . Notice: has a local max where crosses zero going (); has an inflection where crosses zero and bottoms out ().
Tip: When reading a graph of : the height of tells the slope of ; the zeros of mark candidate extrema of ; where is increasing, is concave up.
Going Deeper: Advanced Analysis
Claim: If for every in an interval , then is constant on . Why: Pick any two points in . By the MVT there is a with
so . Since were arbitrary, takes one value throughout . This is the theorem behind “antiderivatives differ by a constant.”
Show for all . Apply the MVT to on : there is a with
Taking absolute values, , so .
Suppose the graph shown is (not ), with .
Then is increasing where : on and ; decreasing on . So has a local max at and a local min at . Since is decreasing for and increasing for , is concave down then concave up, with an inflection point at .
For , . Sign of : positive for , negative on , positive for . Two sign changes give two inflection points, at and . Contrast with , where never changes sign---no inflection despite .
The EVT guarantees a continuous attains its max and min on . Wherever such an extremum occurs at an interior point where is differentiable, Fermat's Theorem forces there. So an absolute extremum can only hide at (i) an interior point with or undefined, or (ii) an endpoint. Checking that finite list of candidates is therefore guaranteed to find the answer.
Minimize the surface area of a closed cylinder of fixed volume . Constraint: . Objective:
Then . Since , this is a minimum. Substituting back gives : the most economical can is as tall as it is wide.
Closest point on () to the origin. Minimize (minimizing minimizes ). Then . The point is with distance .
Big picture: controls slope (rising/falling and where it turns); controls bending (concavity and inflection). Every result in this topic---MVT, the derivative tests, EVT, optimization, curve sketching---is a way of turning information about and into conclusions about .
Formulas, Proofs & Tips
What it means. Maxima and minima hide where the slope is zero; the second derivative says which one it is.
Example. : at , the critical points.
Why it works. At a smooth peak or valley the tangent is horizontal, so . If the slope is increasing, so the curve bends upward and a horizontal tangent must be a minimum; reverses it.
Tip. alone is not enough — has but no extremum. Check a sign change of , or use .
What it means. Somewhere in the interval the instantaneous rate equals the average rate.
Example. For on : , which occurs at .
Why it works. Tilt the graph so the endpoints are level (subtract the secant line). The resulting function has equal endpoint values, so it has an interior max or min, where the derivative is — untilting gives equal to the secant slope.
Tip. Needs continuous on and differentiable on . Rolle's Theorem is the special case .