1. Calculus: Hughs-Hallett Chap 5 Joel Baumeyer, FSC Christian Brothers University Using the Derivative -- Optimization

2. Review: §If f’ > 0 on an interval, then f is increasing on that interval. §If f’ < 0 on an interval, then f is decreasing on that interval. §If f’’ > 0 on an interval, then the graph of f is concave up on that interval. §If f’’ < 0 on an interval, then the graph of f is concave down on that interval.

3. Definition of Maxima and Minima Suppose p is a point in the domain of f: l f has a local (relative) minimum at p if f(p) is less than or equal to the values of f for points near p. l f has a local (relative) maximum at p if f(p) is greater than or equal to the values of f for points near p. §f has a global minimum at p if f(p) is less than or equal to all values of f. §f has a global maximum at p if f(p) is greater than or equal to all values of f.

4. Definition of a Critical Point For any function f, a point p in the domain of f is a critical point if: l f’(p) = 0, or if l f’(p) is undefined f(p) is then called the critical value of f at the critical point p.

5. Theorem (Critical Point) If a continuous function f has a local maximum or minimum at p, and if p is not an endpoint of the domain, then p is a critical point.

6. The First-Derivative Test for Local Max (M) and Min (m) The First-Derivative Test for Local Max (M) and Min (m)Suppose p is a critical point of a continuous function f. §If f’ changes from negative to positive at p, then f has a local minimum at p. §If f’ changes from positive to negative at p, then f has a local maximum at p.

7. The Second-Derivative Test for Local Max (M) and Min (m) § If f’(p) = 0 and f’’(p) > 0 then f has a local minimum at p. §If f’(p) = 0 and f’’(p) < 0 then f has a local maximum at p. §if f’(p) = 0 and f’’(p) = 0 then the test tells nothing.

8. Definition of Inflection Point A point at which the graph of a function changes concavity is called an inflection point. This may be a point where the second derivative: l does not exist, or l equals zero.

9. l’Hopital’s Rule (from Chapter 4) If f and g are differentiable and either of the following conditions hold: 1. f(a) = g(a) = 0 or 2. or if a =  then:

10. Linear Tangent Line Approximation- §Suppose f is differentiable at x = a. Then, for values of x near a, the tangent line approximation to f(x) is: §The expression is called the local linearization of f near x = a. We are thinking of a as fixed, so that f(a) and f’(a) are constant. The error E(x), is defined by and

11. The Tangent Line Approximation of a Function For values of x near a, We are thinking of a as fixed, so f(a) and f’(a) are constant! The expression is a linear function which approximates f(x) well near a. It is called the local lineari- zation of f near x = a.

12. The Bounds of a Function §A function is bounded on a interval if there are numbers L and U such that L  f(x)  U, where L is the lower bound and U is the upper bound. §The best possible bounds for a function f, over an interval and the numbers A and B such that, for all x in the interval, A  f(x)  B and where A and B are as close together as possible. A is called the greatest lower bound and B is called the least upper bound.

13. The Seven Step Paradigm: §1.) I want to and I can §2.)Define the situation §3.)State the objective §4.)Explore the options §5.)Plan your method of attack §6.)Take action §7.) Look back

14. The Book’s Practical Tips: 1. Make sure that you know what quantity or function is to be optimized. 2. If possible, make several sketches showing how the elements that vary are related. Label your sketches clearly by assigning variables to quantities which change. 3. Try to obtain a formula for the function to be optimized in terms of the variables that you identified in the previous step. If necessary, eliminate from this formula all but one variable. Identify the domain over which this variable varies. 4. Find the critical points and evaluate the function at these points and endpoints to find the global maxima and minima.

15. And now for some very significant theorems!

16. §The Extreme Value Theorem If f is continuous on the interval [a,b], then f has a global minimum and a global maximum on that interval. §The Mean Value Theorem If f is continuous on [a,b] and differentiable on (a,b), then there exists a number c, with a < c < b, such that §Local Extrema and Critical Points Theorem Suppose f is defined on an interval and has a local max- imum or minimum at the point x = a, which is not an endpoint if the interval. If f is differentiable at x = a, then f’(a) = 0.

17. §Constant Function Theorem Suppose that f is continuous on [a,b] and differentiable on (a,b). If f’(x) = 0 on (a,b), then f is constant on [a,b]. §Increasing Function Theorem Suppose that f is continuous on [a,b] and differentiable on (a,b). If f’(x) > 0 on (a,b), then f is increasing on [a,b]. If f’(x)  0 on (a,b), then f is nondecreasing on [a,b] §The Racetrack Principle Suppose that g and h are continuous on [a,b] and differentiable on (a,b), and that g’(x)  h’(x) for a < x < b. If g(a) = h(a), then g(x)  h(x) for a  x  b. If g(b) = h(b), then g(x)  h(x) for a  x  b.