University Physics I

Calculus and Analytic Geometry I
Cloud County Community College
Fall, 2012
Instructor: Timothy L. Warkentin
Chapter 04: Applications of Derivatives
Extreme Values of Functions
The Mean Value Theorem
Monotonic Functions and the First Derivative Test
Concavity and Curve Sketching
Indeterminate Forms and L’Hôpital’s Rule
Applied Optimization
Newton’s Method
Chapter 04 Overview
• The rate at which things happen is of fundamental
importance to every field of study in which measurement
is a priority. Derivatives (functions whose range
elements are rates/slopes) are used to describe how
quantities are changing in time.
04.01: Extreme Values of Functions 1
• Extreme range values and their relationship to
open/closed intervals. Example 1
• The Extreme Value Theorem.
• For functions y = f [x] extreme range values are found at
domain values where f ′ = 0, where f ′ is undefined, or at
the endpoints of the domain. Domain values where f ′ = 0
or where f ′ is undefined are called critical points.
• The search for extreme range values begins by
identifying domain values associated with horizontal
tangent lines. Critical domain values are either local
maximums, local minimums or inflection points.
Examples 2 – 4
04.02: The Mean Value Theorem 1
• Rolle’s Theorem (a special case of the MVT). Example 1
• The Mean Value Theorem (MVT) for Derivatives unites the ideas
of Average Rate of Change and Instantaneous Rate of Change (a
consequence of Rolle’s Theorem).
• MVT: There is at least one point in (a,b) where the slope of the
curve is equal to the slope of the secant line on [a,b].
• If y = f [x] is continuous on [a,b] and differentiable on (a,b) then
there is at least one point c in (a,b) at which
f [b]  f [a]
f ' [c ] 
Examples 2 & 3
• MVT Corollary 1: Functions with zero derivatives are constant.
• MVT Corollary 2: Functions with the same derivative differ by a
constant. Example 4
04.03: Monotonic Functions and the
First Derivative Test 1
• Definition of an Increasing/Decreasing function (section
• A function that is increasing or decreasing on an
interval is said to monotonic on that interval.
• Critical points subdivide the domain into nonoverlapping intervals on which the derivative is either
positive or negative. Example 1
• MVT Corollary 3: If the first derivative is
Positive/Negative the function is
• The First Derivative Test (local min/max text).
Examples 2 & 3
04.04: Concavity & Curve Sketching 1
• The graph of a differentiable function is concave
up/down on an interval if the first derivative is
increasing/decreasing (the second derivative is
• The Second Derivative Test for Concavity. Examples 1 &
• Inflection Point: A point where the tangent line exists and
the concavity changes. Examples 3 – 6
• The Second Derivative Test for Local Extrema. Example
• Graphing functions. Examples 8 – 10
04.04: Concavity & Curve Sketching 2
• Understanding y
 f [x] .
1. Graph the function with a graphing utility.
2. Identity any transformative elements.
3. Find the domain and range.
4. Identify any symmetries.
5. Identify any discontinuities.
6. Find any asymptotes or holes.
7. Find any x and y intercepts.
8. Find the first and second derivatives.
9. Find any extreme points and identify local/global maximums/minimums.
10. Find the intervals where the function is increasing and decreasing.
11. Find any inflection points and find the intervals on which the curve is
concave up and concave down.
12. Re-graph the function with any asymptotes and significant points
plotted and labeled.
04.05: Indeterminate Forms and
L’Hôpital’s Rule 1
• Many difficult limit problems can be solved by
application(s) of L’Hôpital’s Rule. If the limit attempted
yields the indeterminate forms 0/0 or ∞/∞ then the
following can be applied. Examples 1 & 3
f [ x]
f '[ x]
 lim
x  a g[ x ]
x a g '[ x]
• This rule can be applied recursively until an acceptable
form is found. Example 2
• Some other indeterminate forms that can be transformed
into the required 0/0 or ∞/∞ are ± ∞/ ± ∞, ∞*0, ∞ - ∞, 1∞,
and ∞0. Examples 4 – 8
04.06: Applied Optimization 1
• Optimization means finding the best possible solution to a
particular problem. Considering that problems often have
an infinite number of solutions, the ability to find the single
best solution for many problems illustrates the power of
• Where an extreme value occurs is not the same as the
extreme value.
• Solving Applied Optimization Problems (textbook
procedure). Examples 1 – 5
04.07: Newton’s Method 1
• This section is not covered.
04.08: Antiderivatives 1
• Definition of the Antiderivative: A function F is an
antiderivative of f if the derivative of F is f. Example 1
• MVT Corollary 2: Functions with the same derivative
differ by a constant (usually written as C).
• The value of C may be determined if an ordered pair
solution of F is known. Examples 2 & 5
• The set of all antiderivatives of f [x] (an infinite set) is
called the indefinite integral of f [x] and is denoted by the
single symbol:
 f [ x] dx . Examples 3, 4, & 6

similar documents