MATH 138 - Calculus II
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These notes are based on a course by Robert Andre (Winter 2004). All errors are responsibility of the author.
1 Review
A few useful identities involving summation notation
-
We call the index of summation.
Let , then
Geometric series:
Reindexing:
Theorem: for all constants .
1.1 Estimating the area of regions bounded by a curve and the -axis
Let on the interval . For the area under the curve, we subdivide the interval into small intervals of size and make rectangles of heights . Then an approximate area under the curve is given by the sum of the area of these approximating rectangles.
That is, and the sample points are , so The actual area is given by allowing the number of rectangles to become infinite (hence, arbitrarily small), thus letting tend to infinity. That is, the actual area is found as Note: the choice of sample points were the right hand sides of the rectangles, which gave us an over-estimate. One could also have chosen the left-hand sides of the rectangles and obtained an under-estimate and both would have the same limit.
2 The Definite Integral
Let be a continuous function on and let for a known integer . Let be a sample point in each interval , then the expression is called a Riemann sumover . The number obtained by is called a definite integral of over . The definite integral is then denoted by (1) where
is the integrand
is the integral sign
are the limits of integration
and this process is called integration. If is a function on such that exists, we say that is integrable on .
Theorem 1. If is continuous on , then it is integrable on (i.e. exists).
Definition 1. If is continuous and non-negative on , then we define the area of the region bounded by and the -axis over as being the positive number obtained by . In the case that is negative, we take the absolute value and if on then on where , then the area is .
Example 1. Using Riemann sums to find a formula for (where ).
2.1 Properties of the definite integral
We provide the following list of properties without proof. Note that, geometrically, these results should be intuitive.
if on , then
if is odd (i.e. ), then
if is even (i.e. ), then
If on then
If for all on , then
Example 2. Show that is in the interval .
Note, for that or equivalently that for all . Hence, also, and our properties guarantee, that
Example 3. Evaluate;
2.2 Average Value of a Function
Suppose is integrable on with . The average value of on is defined as (2)
Example 4. Find the average value of on .
Theorem 2 (Average-value Theorem). Suppose is continuous on , with . Then there exists an such that . That is, a continuous function actually achieves its averages value somewhere within the interval .
Proof. Since is continuous there exist a minimum and maximum at some respectively . Then, certainly for all . Now, from property 9, we have or equivalently (dividing by ) Now, by the intermediate value theorem, there exists such that . ◻
2.3 Fundamental Theorem of Calculus - Part I
Theorem 3 (FTC I). Suppose is continuous on . Let be a function on defined as . Then .
Proof. Let and proceed computing the derivative by first principles. By the average value theorem there is an so that so then as required. ◻
Example 5.
Lemma 1. If and are two functions whose derivative is , then
Proof. Given that , then since the derivative of a constant is 0. ◻
2.4 Fundamental Theorem of Calculus II
Definition 2. A function is called an antiderivative of on an interval if for all .
Theorem 4 (FTC II). Suppose is continuous on and let be any anti-derivative of (i.e. ). Then (3)
Proof. Given that is continuous on and , let so that too. By the previous lemma, then, there is some constant such that . Now, ◻
This theorem says that knowing any anti-derivative allows us to compute any definite integral.
Example 6. Now we are able to compute a few more definite integrals like and
Notation: If is an antiderivative of denote by the family of antiderivatives and call this the indefinite integral of .
2.5 A few antiderivatives
Example 7. Find the reigon bounded by and the -axis over the interval .
Note: won’t work since the function is negative on the second half of this interval. Must use,
Example 8. does not exist since is not continuous at and (3) does not apply.
Definition 3. Let be continuous, we define the differential of , denoted by , as being where and .
Observation: if , then so and so, if then .
3 Techniques of integration
3.1 Integration by Substitution
Theorem 5 (The substitution rule). Let be differentiable and having as its image, the interval . Suppose is continuous on the interval . Then, (4)
Proof. Given that , we are required to show that the general antiderivative of is the same as the general antiderivative (AD) of .
Suppose is an AD of , then .
Now we claim that . Indeed, it remains to show that which is true by the chain rule so the theorem holds. ◻
Remark 1. What the substitution rule is saying is that and thats it!
Example 9. letting so that which is equivalent to , we find
Example 10. Here will will use .
3.2 Integration by Parts
Consider two functions . The product rule says that Integrating both sides of this equation now says that Rearranging, that is or in more compact notation (5)
Recall that
Example 11. Now for a long list of examples with solutions!
Solution: With , so that (using integration by parts - IBP) we find Now, the substitution so that or reveals the above as
Solution: This will require two iterations of IBP. First we will have and so that and . The first iteration becomes For the second term we use so that and the above becomes as required.
Solution: This will also require two iterations of IBP, but has a slightly different solution.
Let so ,
Now for the second term, use so that and then the integral from the second term above becomes Notice that the original integral has reappeared. However, this doesn’t mean we have gone in a circle since other terms have come out. Putting these together reads or in other words,
Solution: Here again we will find a similar solution to the previous problem. Let denote the value of interest, , (for later when we need to rearrange). For IBP, use so that . Now So, rearranging,
3.3 Trigonometric Integrals
Recall and remember the following trigonometric identities:
Now, we will by considering three different cases.
Solution:
when is odd;
Write , then by the substitution and this is easy to evaluate (begin a polynomial).
when is odd;
Write and the substitution
when both and are even;
The identity followed by will bring one of the even powers down to either case (i) or case (ii).
and similarly,
If is even, say , then the substitution and gives
If is odd, then we will substitute with like so
In any other case, we won’t find a closed expression for the integral .
Example 12. Now for a list of examples with solutions!
3.4 Trigonometric Substitution
This method will apply to integrands containing or .
So, if
| Integrand has | substitute | apply identity |
|---|---|---|
| or | ||
| or | ||
Example 13. These ideas will be best demonstrated through a list of examples
Letting so that on the interval we have and , then
The trigonometric substitution here is on so that and , then where the last line is found from the fact that so the hypotenuse is necessarily hence and .
Here we use on so that . Note that this is definite integral so we have to change the bounds of integration. That is, when and when .
Here we will use for so and . Now
3.5 Integration with Partial Fractions
This method is used to solve a rational integrand (i.e. of the form for polynomials and ).
Case 1: , use long division.
Case 2: , factor the denominator and split up with partial fractions.
Example 14. As usual, this is best demonstrated by example.
and here we write This is the linear system and which has solution . So,
Using that has solution , we find that where we have used the substitution to integrate the second two terms.
Here, the partial fractions look slightly different because of the irreducible quadratic factor in the denominator Notice, the linear above the quadratic denominator. This is solved the same way as above and we find that , so
3.6 Non-Elementary Functions
The elementary functions are polynomials, trigonometric, exponential, rational or any combination of these using or composition.
Consider, the function defined by the rule that . Is an elementary function? The answer here is YES! Now, is every function elementary? NO.
For example, is continuous on , so integrable. Then define which has derivative (by FTC I). It can be shown that is not elementary, meaning you can’t find a formula for .
4 Applications of integration
4.1 Areas between curves
Consider a region bounded above by and below by .
Notice that in all three cases thus far, we have the area between and on when is given by the formula
Now, suppose that on and then on . Then
Example 15. Find the area of the region bounded by...
and ;
Solution: Since there is no given interval on which to find the area, we must compute where these two curves meet. That is, solve which is equivalent to so that these curves meet at and . On this interval we find that so the area between them is computed by
and . These curves meet when which has solutions and
Solution 1: Here we integrate along the -axis as follows;
Solution 2: If we tilt our heads, this is actually easier done by integrating along the -axis. The intersection points are and and the area is given by
4.2 Arc Length of a Parameterized Curve
Let be the smooth curve obtained obtained by graphing over the interval . For the arc length of we apply the following simple recipe.
Subdivide the interval into equal subintervals of length
Let
Let be the point on and be the Euclidean distance between the points and . That is, where the last equality holds by the Mean Value Theorem.
Hence, now the approximate length of is given by another Riemann sum! Finally, the arc length of is given by (6)
Example 16. Find the length of the curve defined by on the interval .
Solution:
5 Calculating Volumes
5.1 Cross sectional method
The cross sectional method is often the most practical method used to compute volumes of solids of revolution (a solid obtained by revolving a region bounded by over about the - or -axis).
Principle behind the cross section method
subdivide into equal sub intervals, each of length
Let denote the area of the cross section of the solid at
Then is a sequence of areas of cross sections, each a function of .
If we then keep constant over the interval we obtain an approximation
We now have a sequence of volumes
The approximation of the volume of this solid is then which is a Riemann sum.
So, theoretically, the actual volume of the solid is
Example 17. Using the cross sectional method to calculate the volume of a square based pyramid, with base and height h.
Solution: The side length at can be found using similar triangles as , so then the area at is then . Now, the volume can be computed by
Note that this method would also work using the -axis and integrating with respect to .
The above example was not a solid of revolution. However, there is a nice formula for the cross sectional area (and hence the volume) of a solid of revolution.
Notice, that when is revolved about, say, the -axis, the cross sectional area is a circle, of radius centred at the axis. So then (the area of a circle of radius ). Hence, (7)
If this was about the -axis then .
Example 18. All of the following are solids of revolution.
Show that the volume of a sphere of radius is .
Solution: Here we use the function which is the top half of the circle to be revolved. So then the volume is achieved by integrating along the interval . That is,
Find the volume of a cone with height and radius .
Solution: This will be done along the -axis, since standing cones make more sense than sideways cones. The relationship between and here is that (which can be thought of as the slope of a cone whose tip is at the origin). So the radius at is and the volume is then given by
Now, we are ready for something slightly more involved.
Example 19. Find the volume of the solid formed by revolving the region bounded by and about the (i) -axis, (ii) -axis, and (iii) the axis.
Notice beforehand that the intersection occurs at and . So,
Revolving about the -axis,
About the -axis,
About axis, we need to readjust the integrand.
5.2 Cylindrical Shell Method
The volume of a shell is equal to the outer volume minus the inner volume. Mathematically if represent the inner and outer radius of the cylinder respectively, then where is the average radius and is the thickness of the shell.
Steps for this method:
Suppose we have a region bounded by an suppose it is revolved about the -axis,
Subdivide the interval into equal subintervals ,
Let represent the volume of the cylindrical shell with outer radius , inner radius and height ,
then we have a sequence of volumes of shells which fill our solid so the approximate volume is which is approximately a Riemann sum! Then the volume is given by (8)
Note: This is most often used when there is a hole punched in the solid.
Example 20. Find the volume of the solid that remains after a hole of radius has been bored through the centre of a sphere of radius .
Solution: Now, with we have
Example 21. Using the method of cylindrical shells, find the volume obtained by revolving the region bounded by and about the -axis.
Solution:
In general we have obtained the following two formulas
6 Numerical Approximation
This is used to approximate definite integrals when they cannot be integrated.
There are 3 common methods:
Midpoint Rule: Given , recall that we had a choice of sample points in the interval and we have just been using the right hand side of the interval. Now, consider and finally where
Trapezoidal Rule: Here we use
Simpson’s Rule: Here we use sample points , but our intervals remain of size
Now, because midpoints here are the odd indexed sample points and So,
Example 22. Approximate the definite integral with (i.e. so that using; (i) midpoint rule, (ii) trapezoid rule, (iii) Simpson’s rule.
Solution:
For this, we need the following table of values:
1 .25 0.0625 2 .75 0.5625 3 1.25 1.5625 4 1.75 3.0625 5 2.25 5.0625 6 2.75 7.5625 So,
6.1 Error bounds on approximations
Here we will just provide the error bounds without examining the required analysis.
For ; the error bound is where .
For : Error is
For ; Error is
Example 23. Estimate the error bound when using or approximation for .
Solution: Note that and so that the constant for is and for is Now, and
7 Improper Integrals
The following integrals are called improper. Similarly, is improper (provided, both limits exist).
Warning: Do not do , since one may not converge.
Example 24. Evaluate the improper integral .
Solution:
7.1 Improper integrals of another type
Suppose the function is defined only on the interval with no specified value at . Then we can still define the definite integral ‘improperly’ as The same can be done when is defined on , or even if, say is only defined on (with a hole in the middle of the interval), then Note that the above integral will only converge if both limits exist.
Example 25.
Proposition 1. [Comparison test for improper integrals] Suppose that on . If converges, then also converges.
Furthermore, if diverges, then so does .
Example 26. Does converge?
Soloution: We have on so on or . So so our integral converges by comparison test.
8 Differential Equations
A differential equation (DE) is an equation which contains a derivative expression. The order of a DE is the highest derivative which appears in the equation.
Example 27. is order 2.
Another, simpler, DE is . This is easy to solve (integrate both sides), is a solution.
Lets see a more exciting example.
Example 28. Let be a population function (with for time). After studying the population over time, and discovering a proportionality amongst the and its derivative. That is to say , for some constant . The goal now, is to obtain a formula for . Rearranging slightly is for some positive constant that is determined by specified initial conditions (such as ).
Example 29. Verify that is a solution to in the region .
Solution: With , we compute and . Substituting into the DE, we find
A particular solution to a DE is one without arbitrary constants. That is, any particular function satisfying the DE. The solution from the previous is example is a particular solution.
Example 30. Suppose we want a solution to with [This is called an initial value problem].
Check that is a general solution. Indeed, and Now since , we can solve for the constant as so that is a particular solution to the initial value problem (IVP).
8.1 Separable Differential Equations
If a DE can be expressed in the form , we say it is separable. Equivalently
A separable DE is solved by integrating both sides of this rearrangement. but this requires some justification: If we are given a DE of the form or equivalently . Now let be an anti-derivative of and an anti-derivative of . This equation is then equivalent to the following: Now, this implies that (is constant) and we can find from .
Example 31. Is separable? If so, solve it.
Solution: Yes, it is solvable and it can be re-expressed as This integrates to Now, although this is separable an we managed to integrate it, we find that the solution cannot be explicitly expressed as . In attempt to extract an explicit solution, we treat this as a quadratic equation in . which has solutions, If we had been given the IVP of , then this would imply that the solution be .
8.2 Linear Differential Equations
A linear differential equation is most generally expressed as (9)
Theorem 6. The solution to the linear differential equation (9) is where .
This function is called the integrating factor and is a function satisfying that
Proof. First, verifying that satisfies the above claimed equation. Indeed, expanding the right by the product rule, we have so that, provided , . Integrating this says that
Now, that this holds, the left hand side of our DE is expressed as and now reads, . Hence, integrating this, so as claimed. ◻
Note that this method of solving a DE requires it be of first order (i.e. linear).
Example 32.
Solve the IVP with .
Solution: The integrating factor here is , so and with we find as
Solve the IVP with .
Solution: This is equivalent to or, better, . For the integrating factor . Now,
9 Sequences and Series
Recall, the limit of a sequence: A sequence converges to if for all , there exists such that for all .
Example 33. and and by squeeze theorem, .
An increasing (decreasing) sequence is one such that for all . A monotonic sequence is one which is either strictly increasing or decreasing.
Theorem 7 (Monotone sequence theorem). A bounded monotonic sequence always has a limit (i.e. will always converge).
9.1 Series
Let be a sequence, then is an infinite series. The partial sum of a series is . To evaluate an infinite series we use the limit of the partial sums: If the limit exists, series converges. If limit does not exist, series diverges.
Warning: When discussing series, say , there are two sequences in play. We have the sequence itself and the partial sums , so remember
Example 34.
Consider the geometric series The partial sums are given by and multiplying by says, Subtracting these, we have so that Now, when does a geometric series converge? We must have that exists, which means, in order for a geometric series to converge we must have .
Furthermore, if , then the limit can be computed exactly as . That is, the sum a geometric series is
Example 35. Express the repeating decimal as an infinite series and then as a fraction.
Solution: We have
Letting and , so that
Theorem 8. Suppose and and let . Then, and Note that this theorem requires that both converge.
Theorem 9. If the series converges, then the sequence must converge to 0.
Proof. Given that , consider the sequence of partial sums. Observe, that for each , and now, ◻
9.2 Divergence test
Suppose that is a series. If then the series diverges. This is just the converse of the previous result. Otherwise, divergence test provides no information.
Example 36. Discuss the convergence/divergence of the series
.
Solution: Therefore, the series diverges.
Solution: By partial fractions, we find
This is a telescoping series.
Theorem 10 (Integral test for convergence of a series). Let be a series and suppose is a function on such that
on .
is continuous on
is non-increasing on (i.e. )
for all .
Then,
Proof. Suppose that converges and show that converges. Certainly so which implies convergence.
Suppose now that converges and show the converse. Observe that so and hence so converges. ◻
9.3 Estimating the value of a series
Suppose that is a series proved to be convergent by the integral test (say ).
We would like to approximate by the partial sums and determine what the error will be. Let be the remainder (Note that, we are assuming that our ’s are positive so that the partial sums are an increasing sequence). So, also and we claim that for .
First, it is easy to see that . Now, also since these rectangles are an over approximation of the integral.
Now, So we know that lies in the interval and the error cannot be more than the length of the interval. That is,
Example 37. Use to help calculate .
Solution: With a calculator we find . Notice that is continuous, decreasing on and matches the values of the sequence. So, a good approximation is the midpoint of the interval . That is,
9.4 p-series
Any series of the form where is a fixed positive number.
Theorem 11. If is a -series, then it converges if and only if .
Proof. We first consider the special case that . This series is called the Harmonic series. By the integral test . This diverges and hence, the harmonic series diverges.
Now, consider the case : which diverges if and converges if . ◻
9.5 Comparison test
Theorem 12 (Comparison test). Let be two series with . Then
converges if converges
diverges if diverges.
Proof. Let and represent the partial sums of and respectively. Suppose that . Then since we have for all . Now, and are both monotone increasing sequences and with we have is bounded above by . By monotone sequence theorem, converges.
For the second part, is monotone increasing to infinity. Thus, also is also increasing to infinity. ◻
9.6 Limit comparison test
Theorem 13 (Limit comparison test). Suppose there are two series with both for all . Then
If then either both converge or both diverge.
If and converges, then so does .
If and diverges, then so does .
Corollary 1. If converges then so does .
Proof. Suppose that converges to . We have the inequality By the comparison test, then converges (since ). Assuming that then as required. ◻
Definition 4. If is a series such that converges, we say that is absolutely convergent.
If converges, but does not, then is said to be conditionally convergent.
Any series of the form where ’s are positive, then the series is called an alternating series.
Theorem 14 (Alternating series test). Let be an alternating series. If for all and then the series converges.
Proof. Supposing that and , let denote the partial sums of the series . Note that is monotone increasing and bounded above by . So it remains to show that the limit of is the same as the sum of the series. Note that so thus, the series converges. ◻
9.7 Alternating series estimation
Theorem 15 (Alternating series estimation theorem). If is the sum of an alternating series which satisfies then,
Proof. We know from above that lies between two consecutive partial sums and . It follows that . ◻
Note; the rule that the error is smaller than the first neglected term is valid only for alternating series.
9.8 Ratio test
Let for a series . Then
if , the series is absolutely convergent and hence convergent
if or then the series is divergent
if or does not exist then the test is inconclusive.
9.9 Root test
Let be a series. Then
if then is absolutely convergent,
if or the series is divergent
and otherwise, if the test is inconcolsive
10 Series testing strategies
The following is a recipe for testing convergence of series.
Check if is geometric, harmonic, p-series or telescoping
Is the ? If not, then the series diverges (by divergence test). Otherwise, convergence is still unknown
Does resemble or for large ? If so, try the comparison test, or limit comparison test with geometric series or a -series
If for some positive, decreasing continuous function , try the integral test
If there are powers of or the ratio test is probably a good idea.
This test may result in the series diverges with or so there would be no need to proceed with alternating series.
This may show that converges absolutely (when ) hence converges
if or doesn’t exist, this test has failed and says nothing
Try the Root test, especially if you see powers of !
If or series diverges
if it converges absolutely and hence converges
if , or does not exist the try something else because we still don’t know
if both ratio and root test have already failed, or it is clear that is divergent, try (if series is alternating) the alternating series test incase it is conditionally convergent.
Error bounds:
if series converges by the integral test, use the integral formula for approximate value of series.
if the series converges by the alternating series test, use the alternating series estimation theorem to approximate the value.
11 Power series
A power series centered at is a series of the form with a variable. This series differs in values because of the variable . This means that certain values cause series to converge and some won’t. This should give the impression that a power series is a function whose domain is a collection of values for which the series converges. When studying these, we will be interested in finding an elementary function such that as well as determining its domain.
Observations: We already know that converges to for while it diverges everywhere else. So, we could say that , centered at zero converges to the function on the interval and diverges elsewhere.
The function is a polynomial. Recall, from Taylor polynomials that if that . Thus, a power series can be viewed as a function whose curve is a limit of a sequence of polynomials.
Also notice that a power series always converges for .
Here, we will mainly discuss two things;
For what values of does a power series converge? (this is called the radius and interval of convergence
To what function, if any, does it converge to?
Theorem 16. The power series converges either for , for all or there is a positive number such that the series converges for all and diverges for all .
Note: When a power series is known to converge for all , one must manually determine convergence at the endpoints of this open interval.
Proof. Given the power series , suppose we define . Applying the ratio test to . Then this converges for or, equivalently, . So to say that . ◻
Remark 2. The above theorem states convergence on intervals centered at . This is called the interval of convergence. Series may or may not converge at the endpoints of this interval. The . If the power series converges to a function, we say for all
Example 38. Discuss the convergence of the following power series
Solution: Here so or . At the endpoints; when this is when this becomes which is known to converge! Thus, the interval of convergence is .
Solution: Here we find hence which implies radius of convergence is infinite and series converges for all values of .
11.1 Functions as power series
Using that as a basis, we can find other functions expressed as power series!
For example,
and the interval of convergence is or, .
with interval of convergence which is really just .
with radius of convergence or
Now that we can deal with everything of this form, we will need a new style.
Theorem 17. Suppose has radius of convergence and suppose that . Then is differentiable of and and both of these resulting power series have for their radius of convergence.
Example 39. Show that with .
Solution:
and radius of convergence .
for .
11.2 Taylor and Mclaurin series
Suppose has power series representation . What do the ’s look like?
Theorem 18. Let on , then That is to say
Example 40. We know that which implies that so the derivative of evaluated at zero is .
Definition 5 (Taylor series). Let be a function which is differentiable infinitely many times, then the series is called the Taylor series generated by centred at .
Any Taylor series centred at 0, is called a McLaurin series.
Example 41.
is the Mclaurin series for .
Find the McLaurin series generated by and determine the interval of convergence.
Solution: We need only determine . So
Notice that there exists functions which generate taylor and McLaurin series that do not converge to the original function. For example, the piecewise defined function has a McLaurin series of 0, but this function is not the zero function.
The degree taylor polynomial for , centred at is defined as the truncated version of its Taylor series . These are the partial sums of the Taylor series and again we can define the remainder .
We have that
To show that , we will use a tool called Taylor’s inequality.
Theorem 19. Let be a Taylor series with radius of convergence . Then can be bounded above in the following way:
If on , then If we can show that for all , then
Example 42. Recall, Mclaurin series of
has infinite radius of convergence
(since
since
converges by divergence test).
Show that converges to .
Solution: Consider any interval . Since is increasing let . Then Taylors inequality guarantees that . Now, as required.
Example 43. Find the McLaurin series generated by .
Solution: since the derivatives of sine are and repeat every four, we find the values of these derivates to be and repeat every four. Hence, then the series is given by and
Does the series generated by converge to ?
We have and for all . Thus, So the Taylor series generated by converges to for all .
Note that if you wanted to approximate near , choose .
Example 44. Estimate with error .
Solution: Recall and we know that . That is, Try , and find that . Thus, .
Example 45. Find the McLaurin series for .
Solution:
Theorem 20. Let be two McLaurin series with radii of convergence and respectively. Then where has interval of convergence .
Example 46. Find the Mclaurin series for .
Solution: which implies and .
Everyone should know the following list of Taylor expansions
12 Applications of Taylor and McLaurin series
Find the sum of the series .
Approximate the integral with error less than .
Solution: This is an alternating series, so the error bound for is . Letting , then . Therefor is appropriate and
Approximate the integral with error less than .
Solution:
implies so
When , this is .
12.1 Binomial series
Recall, if that where .
Definition 6. For and real number and a positive integer, define as follows:
Theorem 21 (Binomial Series Theorem). Let . Then the McLaurin series for with interval of convergence .
Example 47. Find a McLaurin series for .
Solution:
So, now the McLaurin series for we can compute since we know the series! Indeed,
12.2 One last application
The pendulum of length ;
We would like to approximate given
Express
Then