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The Six Pillars of Calculus

The Pillars: A Road Map
A picture is worth 1000 words

Trigonometry Review

The basic trig functions
Basic trig identities
The unit circle
Addition of angles, double and half angle formulas
The law of sines and the law of cosines
Graphs of Trig Functions

Exponential Functions

Exponentials with positive integer exponents
Fractional and negative powers
The function $f(x)=a^x$ and its graph
Exponential growth and decay

Logarithms and Inverse functions

Inverse Functions
How to find a formula for an inverse function
Logarithms as Inverse Exponentials
Inverse Trig Functions

Intro to Limits

Overview
Definition
One-sided Limits
When limits don't exist
Infinite Limits
Summary

Limit Laws and Computations

Limit Laws
Intuitive idea of why these laws work
Two limit theorems
How to algebraically manipulate a 0/0?
Indeterminate forms involving fractions
Limits with Absolute Values
Limits involving indeterminate forms with square roots
Limits of Piece-wise Functions
The Squeeze Theorem

Continuity and the Intermediate Value Theorem

Definition of continuity
Continuity and piece-wise functions
Continuity properties
Types of discontinuities
The Intermediate Value Theorem
Summary of using continuity to evaluate limits

Limits at Infinity

Limits at infinity and horizontal asymptotes
Limits at infinity of rational functions
Which functions grow the fastest?
Vertical asymptotes (Redux)
Summary and selected graphs

Rates of Change

Average velocity
Instantaneous velocity
Computing an instantaneous rate of change of any function
The equation of a tangent line
The Derivative of a Function at a Point

The Derivative Function

The derivative function
Sketching the graph of $f'$
Differentiability
Notation and higher-order derivatives

Basic Differentiation Rules

The Power Rule and other basic rules
The derivative of $e^x$

Product and Quotient Rules

The Product Rule
The Quotient Rule

Derivatives of Trig Functions

Necessary Limits
Derivatives of Sine and Cosine
Derivatives of Tangent, Cotangent, Secant, and Cosecant
Summary

The Chain Rule

Two Forms of the Chain Rule
Version 1
Version 2
Why does it work?
A hybrid chain rule

Implicit Differentiation

Introduction
Examples
Derivatives of Inverse Trigs via Implicit Differentiation
A Summary

Derivatives of Logs

Formulas and Examples
Logarithmic Differentiation

Derivatives in Science

In Physics
In Economics
In Biology

Related Rates

Overview
How to tackle the problems
Example (ladder)
Example (shadow)

Linear Approximation and Differentials

Overview
Examples
An example with negative $dx$

Differentiation Review

How to take derivatives
Basic Building Blocks
Advanced Building Blocks
Product and Quotient Rules
The Chain Rule
Combining Rules
Implicit Differentiation
Logarithmic Differentiation
Conclusions and Tidbits

Absolute and Local Extrema

Definitions
The Extreme Value Theorem
Critical Numbers
Steps to Find Absolute Extrema

The Mean Value and other Theorems

Rolle's Theorems
The Mean Value Theorem
Finding $c$

$f$ vs. $f'$

Increasing/Decreasing Test and Critical Numbers
Process for finding intervals of increase/decrease
The First Derivative Test
Concavity
Concavity, Points of Inflection, and the Second Derivative Test
The Second Derivative Test
Visual Wrap-up

Indeterminate Forms and L'Hospital's Rule

What does $\frac{0}{0}$ equal?
Examples
Indeterminate Differences
Indeterminate Powers
Three Versions of L'Hospital's Rule
Proofs

Optimization

Strategies
Another Example

Newton's Method

The Idea of Newton's Method
An Example
Solving Transcendental Equations
When NM doesn't work

Anti-derivatives

Antiderivatives
Common antiderivatives
Initial value problems
Antiderivatives are not Integrals

The Area under a curve

The Area Problem and Examples
Riemann Sum Notation
Summary

Definite Integrals

Definition of the Integral
Properties of Definite Integrals
What is integration good for?
More Applications of Integrals

The Fundamental Theorem of Calculus

Three Different Concepts
The Fundamental Theorem of Calculus (Part 2)
The Fundamental Theorem of Calculus (Part 1)
More FTC 1


What is integration good for?

As we have seen, definite integrals can be used to compute area, just as derivatives can be used to compute slopes of tangent lines. But there is much more to derivatives than slopes of tangent lines, and there is much more to integrals than area. Integrals can be used to compute any bulk quantity.

To compute any bulk quantity:
  1. Break it up into small pieces (of size $\Delta x$) that are easier to understand.
  2. Estimate the contribution $f(x)\, \Delta x$ of each piece.
  3. Add up the pieces to get the Riemann Sum $\displaystyle\sum_{i=1}^n f(x_i^*) \,\Delta x$.
  4. Take a limit to slice finer and finer, infinitely fine, to get the exact answer: $$\int_a^b f(x) \,dx = \lim_{n\to\infty} \,\sum_{i=1}^n f(x_i^*) \,\Delta x.$$

Example: Distance

Suppose that we know a particle's velocity as a function of time. If the velocity is constant, then it's easy to find the distance traveled: $$ \hbox{Rate} \times \hbox{Time} = \hbox{Constant Velocity} \times \hbox{Time} = \hbox{Distance}.$$ If the velocity is almost constant, then we can get a good approximation by pretending that it is constant. If the velocity varies a lot, then we break our time interval into little sub-intervals on which the velocity doesn't change much, estimate each one, and add up the pieces. This is exactly the same strategy that we used for area under a curve.

Example 1: Find the distance traveled by a person walking at 2 MPH from 1:00 PM to 4:00 PM.

Solution: 3 hours at 2 MPH makes $3 \times 2 = 6$ miles.


Example 2: Find the approximate distance traveled by a person walking at velocity $v(t)=2 + 0.02 t$ MPH between $t=1$ (o'clock) and $t=4$ (o'clock).

Solution: The velocity doesn't change much between 1 and 4 PM, so we approximate our velocity as $v(1)=2.02$ and compute $(4-1)v(1) = 3(2.02)=6.06$ miles traveled.

The answer in Example 2 is an underestimate, a little bit too small, since the velocity goes up from $v=2.02$ at $t=1$ to $v=2.08$ at $t=4$. If we wanted an overestimate of the area, we would use the value of $v(t)$ at the right endpoint instead: $(4-1)v(4)=3(2.08)=6.24$. And if we wanted a more accurate guess, we might use the midpoint $f(2.5)=2.05$ and estimate the area as $(4-1)v(2.5)=3(2.05)=6.015$. But whether we use the left endpoint, the right endpoint, or the midpoint, we get roughly the same answer, since the velocity just isn't changing very much between $t=1$ and $t=4$.

If the paragraph and examples above look familiar, it is because this is exactly like finding the area under $y= 2 + 0.02x$ between $x=1$ and $x=4$. Only, in this case, the function is $v$ instead of $f$, and the variable $t$ instead of $x$, but it's the same calculation.

To compute the distance traveled between time $t=a$ and time $t=b$ from the function $v(t)$, we
  1. Break our time interval into $n$ pieces, so that the velocity is practically constant in each piece.
  2. The distance traveled in the $i$-th time interval is approximately $v(t_i^*)\Delta t$.
  3. Add these up and take a limit to get a total distance of $$\int_a^b v(t) dt = \lim_{n\to\infty} \sum_{i=1}^n v(t_i^*) \Delta t,$$ where we may as well take $t_i^*$ to be $t_i$.


It follows that distance is the area between the velocity curve and the $t$-axis. 

DO:  What does it mean if the velocity is negative?  How would that affect the distance traveled?  Sketch a graph of a velocity curve that is positive for some times and negative for others to help you see what is happening.