MATH 138 - Calculus 2
MWF 11:30AM - 12:20PM 
MC 4021
Katy Howell Escobar

1 | Integration

1.1 | The Definite Integral

Regular Partition: Consider an interval with and . If we define , Then the points separate into subintervals of equal width . We call this a regular partition of

Riemann Sum

Definite Integral

Right and Left Endpoint Riemann Sums

Converting Function to Riemann Sum

Example: Evaluate

Right-handed Riemann sum: (IMPORTANT) This is the same thing as

Summation Formulas

1.2 | Properties of the Definite Integral

Integral Properties

  1. Constant Multiple
  1. Sum / Difference
  1. Squeeze: for all
  1. Positive: for all
  1. Greater: for all
  1. Absolute Value:

Definite Integrals: Special Cases Zero

Inverted range

(Separating the Domain of Integration)

Even and Odd Functions: Let be a bounded integrable function defined on If is odd , then

If is even , then

Function parity is just like number parity: odd / odd = even / even = even, else it’s odd

1.3 | Average Value of a Function

Definition: Average Value of a Continuous Function:
If is continuous on , then the average value of on is

Average Value Theorem (AVT) - similar to VT If is continuous on , then there exists at least on such that

1.4 | FTC Part 1

Power Rule for Antiderivatives For all

FTC I: If is continuous on an open interval containing , then

Extended FTC I (Chain Rule): If is continuous and are differentiable, then

Example: Evaluate

\frac{d}{dx}\int_{5x}^\sqrt{x}\cos(t^2)dt=\cos(x)\cdot\frac{1}{2\sqrt{x}}-\cos(25x^2)\cdot5

1.5 | FTC Part 2

The Antiderivative Theorem: If are antiderivatives of a function on an open interval , there exists a constant such that

FTC II:

1.6 | The Substitution Rule

Substitution Rule / Change of Variables If and are functions such that is continuous on an interval and is continuous on the range of

Example: Evaluate

Example: Evaluate

Example: Evaluate

Example: Evaluate

Example: Evaluate

Example: Evaluate

Example: Integrate

Theorem: Integrating Let . If , then

Theorem: Substitution Rule for Definite Integrals If are functions such that is continuous on an interval and is continuous on the range of , then

Example: Integrate

1.7 | Trig Substitution

Theorem: Antiderivatives of Trig functions

Example 1: Consider

Let

Motivation for picking :

Writing in terms of :

Example 2: Consider

Let

Example 3:

Let

hyp = x adj = 2 opp =

Example 5:

\int_0^\sqrt{3}\frac{x}{(1+x^2)}dx

Let

Example 6:

Aside:

Let

1.8 | Integration by Parts

Derivation

Theorem: Integration by parts

Example 1:

Example 2:

1.9 | Partial Fractions

Robert Garbary

Goal: Find a derivative of

If , write

Ex:

Plan: Find such that

Spoiler: It turns out a unique always exist as long as

Method 1: Comparing coefficients

Method 2:

Theorem: Cool stuff

Ex:

Ex:

1.10 | Improper Integrals

Definition: Improper Integrals Let , assume is integrable on for all . Let .

  • If exists (it converges to a number), we say converges to L.
  • If doesn’t exist, we say it diverges.

Type 1 Improper Integral

One of the bounds is Ex:

Note that the 2 doesn’t affect whether or not this converges, but what it converges to.

Ex:

Ex:

VERY IMPORTANT NOTE:

Ex: Let . for which does the following diverge:

Case 1:

Case 2:

Theorem: Type-1 p-integrals:

converges if and only if . If it converges, it converges to .

Theorem: Improper Type 2 p-integral

  1. J converges if and only if
  2. If J converges, it converges to

Let

By Improper Type-1 p-integral Theorem, Thus converges, and it converges to

Type 2 Improper Integral

Definition: Let with . Assume is integrable on for all . Assume is “bad” at a (or b)

If is bad , we define

Ex:

Solution

Ex:

Solution

1.11 | Area Between Curves

Bounded area of :

If they intersect at :

Example: On , find the area bounded by

Vertical integrals:

Example: Find the area bounded by

1.12 | Volumes of Solids of Revolution

Volume of Revolution (Disc)

Ex: Fix

Proves the volume of a sphere!

Volume of Revolution (Washer)

Where is the big radius, is the small one

Ex: Consider the area between

Ex: Consider rotated around

Ex: Consider

Ex: Consider , revolved around the axis

Ex: Consider a cone with base and height revolved around the y axis

2 | Differential Equations

2.1 | Introduction to Differential Equations

Definition: Differential Equations

  • Differential Equation (DE) = equation involving an unknown function and it’s derivative
  • Ordinary Differential Equation (ODE) = single-variable functions
  • Partial Differential Equation (PDE) = multivariable functions (multiple inputs)

Definition: Order of a DE

  • The order of a DE is the highest derivative that appears in the equations

Definition: Linearity

  • An ODE is called linear if it only contains linear functions on

Definition: General and Particular Solution

  1. General Solution = Complete collection of solutions to a DE including arbitrary constants
  2. Particular Solution = One where all arbitrary constants have been specified

Ex: What constant functions () satisfy:

Solution: We know

Ex: Is a solution to the DE

Solution: Yes

2.2 | Separable Differential Equations

Definition: A first-order differential equation is said to be separable if it can be written in the form

Method: Solving a separable DE

  1. Determine any solutions with
  2. Find the solutions by evaluating the following. If possible, isolate is a function of in the resulting equation.

Ex:

Solution: Step 1: , no constant solution Step 2: Rearranging and integrating

Checking:

Ex:

Solution:

Step 1: , no constant solution Step 2: Rearranging and integrating

Imagine we know that

Ex

Solution

Ex:

Solution

Ex:

Solution: Let .

NOTE: we divided both sides by , so is also a solution.

2.3 | Linear First-Order Differential Equations

Definition: A linear differential equation of order has the form

where

Definition: A first-order linear DE of the form

is said to be in standard form.

Example: Consider the first order linear DE:

Multiply by on both sides, so that the left hand side becomes the derivative of the right side

NOTE: do not take the term and bundle it into a new constant!

Definition: Integrating Factor Given a linear DE of the form , the integrating factor for would be

In the example ,

Method: Solving a first order DE

  1. Divide by to write the DE in standard form: .
  2. Multiply both sides of the equation by the integrating factor .
  3. Rewrite the left-hand side of the resulting equation as .
  4. Integrate both sides of the equation with respect to x.
  5. Isolate for y.

2.4 | Applications of Differential Equations

Example: Tank has 1000L salt water, initially 0.1kg/L. Salt water of concentration 0.3 kg/L flows in at 10 L/min. Assume ceteris paribus.

1000L = constant volume 0.1 kg/L = initial concentration 1000L x 0.1kg = 100kg of salt

Let = amount of salt (kg) in the contain at time minutes

Concentration is

Solving the separable DE:

Sub

Science: Newton’s Law of Cooling: An object’s temperature changes at a rate proportional to

Example: Find the general solution to Netwon’s Law of Cooling

Example: If the object went from 0C to 5C in 10 minutes, solve the ODE

Solving the general formula:

Solution:

3 | Numerical Series

3.1 | Introduction to Series

Definition: Series Let be a sequence of real numbers. An infinite series be a symbolic expression of the form

Definition: Partial Sums Given an infinite series , we define its sequence of partial sums, as

is called the -th partial sum of the infinite series.

Definition: Geometric Series A geometric series is a series of the form

The -th partial sum of the geometric series is

Theorem: Geometric Series Test Let be a geometric series, where

  1. If , then converges to
  2. If , then diverges

Example: The series

Converges to

Definition: Harmonic Series

Telescoping Example: The series

Converges to

3.2 | Arithmetic Properties of Series and the Divergence Test

Definition: Tail Given an infinite series , let denote its -th partial sum. The difference

Is called a tail of the infinite series

Theorem: Tail Convergence / Divergence Theorem Let be a sequence and let be a positive integer.

  1. If converges, then its tail also converges for each
  2. If the tail converges for some , then also converges (There’s also a Tail Divergence Theorem which is just the contrapositive)

Theorem: Convergence Theorem If converges, then

Theorem: Divergence Test (n-th term divergence test) If , then diverges

Katy’s examples 1: converges

2: converges

3: diverges 4: diverges

5: converges, p series

6: diverges??

Example: What is the value of if

Solution:

Evaluating the +

Evaluating the -

So the solution is the +

3.3 | Integral Test

Definition: An infinite series is said to be:

  • Positive / Nonnegative if for all
  • Strictly positive if
  • Eventually positive if there exists a positive integer such that for all
  • Eventually strictly positive for … take a wild guess

Lemma: Let be an eventually positive series. Let denote its -th partial sum. Then there are only two possibilities.

  1. If the sequence of partial sums is bounded from above, the converges
  2. If the sequence of partial sums is not bounded from above, then diverges to

Theorem: Integral Test Suppose a function is continuous, positive, and decreasing on the infinite integral for some positive integer . Then,

  1. If converges, then the infinite series converges
  2. If diverges, then the infinite series diverges to

Example:

Using the integral test:

Example:

Integral Test:

Example:

Using the integral test, since is continuous and positive for

Definition: p-series

  • converge
  • diverge

Example: The following series converges because

Theorem: Integral Test Estimation Theorem Suppose that a function is continuous, positive, and decreasing on the infinite interval for some positive integer , and that converges so that for some real number by the integral test. Let denote the -th partial sum. Then for any integer ,

We denote

Example: How many terms are needed to approximate with an error of at most 0.001

Solution:

Example: Find an upper bound on the error if we choose the partial sum to estimate

Solution:

3.4 | Comparison Test and Limit Comparison Test

Theorem: Comparison Test For any two sequences

  • If converges, then any smaller series converges
  • If diverges, also diverges

Examples:

Solution: Since converges (p-test, ), then by comparison, so does

Solution:

Since diverges (Harmonic series, p-series), then by comparison, also diverges

Solution:

Since diverges, BUT is less than , we get no information about it!

Theorem: Limit Comparison Test For any two sequences , , let

  1. If either both converge or both diverge
  2. If , there exists a positive integer such that for all . Consequently:
    1. If converges, then does too.
    2. If diverges, then does too.
  3. If , then there is a positive integer such that for all . Consequently:
    1. If converges, then does too.
    2. If diverges, then does too.
  4. If , we don’t know anything

When to use LCT?

Almost geometric series:

Examples:

Solution:

By LCT, since diverges, so does

Solution:

Since converges (geometric series), by LCT, so does

3.5 | Alternating Series Test

Definition: Alternating Series Let be a strictly positive series. An alternating series is an infinite series that is in one of the following forms:

Theorem: Alternating Series Test converges if

  1. is eventually decreasing; there exists a positive integer such that for all

Example:

  1. BY AST this converges

Example

  1. Use derivative to find decreasing

Thus, is decreasing on

Example

  1. - criteria fails!

Use Divergence Test:

Since , this diverges!

Theorem: Alternating Series Estimation Theorem Let be a sequence that satisfies the Alternating Series Test, so that

Let denote the -th partial sum of , and denote the -th partial sum of . Suppose , where is the positive integer in part ii) of AST hypothesis. Then,

  1. and
  2. If is even, then is an underestimate of and is an overestimate of
  3. If is odd, then is an overestimate of and is an underestimate of

Example: Find an upper bound on the remainder if we use to approximate

How many terms are needed to approximate with an error of most

Is the 121st partial sum of an over or underestimate? is over, is under, so is an overestimate

3.6 | Absolute and Conditional Convergence

Definition: Absolutization

Theorem: Absolute Convergence Test

Example:

So this series is conditionally convergent!

Example:

Consider

Comparison test:

Since converges (p-series), we have that neither diverges to or . Thus, it converges

Order to apply tests

  1. Divergence test
  2. Check for absolute convergence
    1. p-series
    2. geometric
    3. comparison
    4. integral
  3. Check for conditional convergence
    1. alternating series

Examples:

  1. Divergence test fails (limit = 0)
  2. Comparison test with

By LCT since converges (p-series), this also CONVERGES ABSOLUTELY

  1. Divergence test fails
  2. Integral test with
  1. Divergence test fails
  2. LCT with
  1. AST

Thus, this series CONVERGES CONDITIONALLY

3.7 | Ratio Test and Root Test

Theorem: Ratio Test Let be a positive integer. Suppose that is a sequence satisfying for every . Let be the following, and suppose that either or

  1. If , then converges absolutely
  2. If , then diverges
  3. If , then the test is inconclusive

Example

Example:

Example

Example:

Example:

Theorem: Root Test Let be the following, and suppose that or

  1. If , then converges absolutely
  2. If , then diverges
  3. If , then the test is inconclusive

Example:

Comparing Values

Series Recap

  1. Sum of Geometric and Telescoping Series
  2. Divergence Test (any series) 2. 3. Use this first
  3. Integral Test (positive series)
    1. Last resort, must be continuous, positive, decreasing
  4. P-series 2. 3. Good for comparison and limit comparison
  5. Comparison Test
    1. Polynomial / Polynomial
    2. Also last resort, LCT usually better
  6. Ratio Test (any series)
    1. Factorials / Exponents
  7. Root Test (any series)
    1. Powers of n
  8. Alternating Series 2. Only proves conditional convergence

4 | Power Series

4.1 | Introduction to Power Series

Definition: Power Series A power series is a series of the form (centered at 0)

Or (centered at a)

The domain of a power series is the collection of all for which the power series converges

Notes:

  1. When , the term is
  2. If the first few coefficients are zero, , then

Example: Find the domain of

Ratio test:

Domain:

Example: Find the domain of

Ratio test:

By the ratio test, If converges by AST If diverges by p-series

Theorem: Power Series For any power series , there are only three possibilities

  1. The series converges only when
  2. The series converges for all
  3. There exists such that the series converges absolutely for , diverges if , and may converges or diverge if

Definition: Radius and Interval of Convergence The in the previous theorem is called the radius of convergence, and the domain / interval of convergence is the interval on which the power series converges

  1. - check endpoints in this case

Find the radius and intervals of convergence: Q1

Q2

Q3

4.2 | Representing Functions as Power Series

Theorem: Abel’s Theorem Let denote the interval of convergence for the power series function

Then is continuous on

Properties Let and Let be the radii and intervals of convergence for respectively. Property 1:

  • If , then and
  • If , the

Property 2:

Property 3:

, and if

Example: Express as a power series and find the interval of convergence.

Example:

Radius:

Example:

Radius

Example:

Radius

Example

Radius

Example

4.3 | Differentiating and Integrating Power Series

Theorem: Let with radius of convergence . Then, is differentiable (and continuous and integrable) on . In addition:

Example:

diverges by divergence test diverges by divergence test

Example

To test endpoints, choose (this doesn’t affect convergence / divergence)

Diverges by LCT

Converges by AST

Example:

Let Endpoints:

Diverges by LCT

Converges by AST

Theorem:

Proof:

4.4 | Taylor Series and Taylor Polynomials

3b1b Explanation

Pendulum approximation

Taylor Series approximate non-polynomial functions with polynomials.

Ex: Approximate with a function We know that , so

We want the derivative of to be similar to the derivative of

We want the second derivative of to be similar as well

Observe:

  • We can add a term if we wanted to get even closer
  • There are many factorial terms ()
  • Adding new terms doesn’t change the previous terms
  • Observations about higher-order derivatives make the approximation more accurate

Taylor Polynomial

Taylor Polynomial around a point :

Example: Approximating around 0

Example: Approximating the integral function of

Base = Height = Triangle =

Does it make sum to keep approximating without stopping?

  • Taylor Series = Infinitely long Taylor Polynomial
  • Certain series converge to a certain value
  • For instance, the Taylor Polynomial for converges to at all inputs
  • The Taylor Polynomial for converges to on , otherwise it diverges
  • This is called the Radius of Convergence
  • Lagrange Error Bound, convergence tests, etc.

Textbook

Definition: The -th derivative of will be denoted by

Theorem: Uniqueness of Power Series Representation Suppose that has a power series representation centered at , meaning

holds for all satisfying , where . Then,

Definition: Taylor and Maclaurin Series Let be differentiable arbitrarily many times at , i.e., is a well-defined real number for every nonnegative integer . The power series

is called the Taylor Series for centered at . The Maclaurin Series is a Taylor Series centered at 0.

Definition: Taylor Polynomial Assume that is -times differentiable at . The -th degree Taylor Polynomial for centered at is

We note that is the -th partial sum of the Taylor series for centered at

Theorem: For every integer , we have that

Theorem: Lagrange Remainder Formula Let be a nonnegative integer. Suppose that is continuous on an open interval that contains . If , then there exists a real number such that

Theorem: Taylor’s Inequality Let be a nonnegative integer. Suppose that is continuous on an open interval that contains . If for every , then we have

Theorem: Convergence Theorem for Taylor Series Assume that has derivatives of all orders on an open interval that contains . Further assume that there is a constant such that for every nonnegative integer and for every . Then for every

4.5 | Some examples of Taylor Series

Examples: Taylor Series

Write a Maclaurin Series for

Write a Maclaurin series for

Known Power Series

Example: Find the Maclaurin Series and radius for

Example: Find the first three nonzero terms of the Maclaurin Series for

Example: Write the following as an infinite sum

Examples: Find the Taylor Series and interval of convergence for:

Note: all odd have 0 as a coefficient, all even have 2

Ex: Determine an explicit formula of the power series

Examples: Taylor Polynomials

Find the 2, 4, 6th degree Taylor Polynomial centered at for

Find the 4th degree Taylor Polynomial centered at for

Approximate the function by a Taylor polynomial of degree 2 at How accurate is this when ?

Finding Error

4.6 | Binomial Series

Example: Binomial Coefficient Let be a real number and let be a strictly positive integer. We define

We note that the numerator of has factors. We also define

Remark: Choose Notation

The Binomial Theorem states that

Theorem: Let be a real number and be a strictly positive integer. Then

Theorem: Generalized Binomial Theorem Let be a real number. If , then

If and is not a nonnegative integer, then this sum diverges.

Prove: If , then

Prove: Let then

Ex: Write as a power series.

Ex: Find the Maclaurin series for the function

4.7 | Applications of Taylor Series

Ex: Determine 2 different series that can be used to evaluate the following functions

  1. geometric
  2. with derivative

Ex: Find the values of the following series

Ex 2

Ex 3

Ex: Find the sum of

Ex: Express as a power series

Ex: How many terms to get this approximation within an error of

Ex: Evaluate as power series

Ex: Evaluate

Ex: Evaluate

Ex:

Ex:

Ex:

4.8 | Big-O Notation

Definition: Big-O Notation Let denote a real number or . Assume that are two functions that are defined for all real values that are near but are not necessarily when . More precisely, if , we assume that are both defined for all in the union

where is some strictly positive real number. If , we assume that are both defined for all in some open interval , where . We write

if there exists a real constant such that for all ,

Ex: Express in Big-O notation

Ex: Show that if then

Ex:

Ex:

  1. F
  2. T
  3. F
  4. F
  5. T

Ex: Consider

Theorem Let denote a real number or . If as and as , then as .

Theorem Let m and n be nonnegative integers. As , the following statements hold. (i) (ii) , where . (iii) . (iv) when . (v) for any real constant C. (vi) when .

Theorem: Taylor’s Inequality, the Big-O Version Let be a nonnegative integer. Suppose that is continuous on an open interval that contains . If there is a real constant such that for every , then

as . Moreover, if is a polynomial of degree such that

as , then

Ex

Ex

thanks katy howell escobar!