Representation of functions as power series

Size: px
Start display at page:

Download "Representation of functions as power series"

Transcription

1 Representation of functions as power series Dr. Philippe B. Laval Kennesaw State University November 9, 008 Abstract This document is a summary of the theory and techniques used to represent functions as power series. Representation of Functions as Power Series (8.6). Theory In this section, we develop several techniques to help us represent a function as a power series. More precisely, given a function f (x), we will try to nd a power series c n (x a) n such that f (x) c n (x a) n. Part of the work will involve nding the values of x for which this is valid. Part of the reason for doing this is that a power series looks like a polynomial (except that it has in nitely many terms). Polynomials are among the easiest functions to work with. They are easy to di erentiate, integrate,... So, if f is a complicated function, replacing it with a power series amounts to replacing it with a polynomial. Therefore, working with f becomes easier. There are some technical di culties to resolve, we will address those as we develop the technique. First, we will look at techniques which will allow us to obtain a series representation by using known series representations. The techniques involved are substitution, di erentiation and integration. Then, we will learn a technique which will allow us to nd a series representation for a given function f directly, without having to use known series. We now look at each technique (substitution, di erentiation and integration) in details, using examples. At this point, we only know the following series representation: x + x + x + + ::: in ( ; ) x n

2 When nding the power series of a function, you must nd both the series representation and when this representation is valid (its domain).. Substitution We derive the series for a given function using another function for which we already have a power series representation. Then, we do the following:. Figure out which substitution can be applied to transform the function for which we know the series representation to the function for which we want a series representation.. Apply the same substitution to the known series. This will give us the series representation we wanted. 3. The domain of the new function is obtained by applying the same substitution to the domain of the known series. Example Find a power series representation for f (x) and its domain. + x We use the representation of, replacing x by x. We obtain: x + x ( x) + ( x) + ( x) + ( x) 3 + ::: x + x + ::: ( ) n x n The series representation for was valid if jxj <. If we apply the same x substitution, we see that this representation is valid if j xj < or jxj <. In other words, the interval of convergence is also ( ; ). Example Find a power series representation for f (x) x. Proceeding as above and remembering that x X x n, we have: x x n x n + x + x 4 + :::

3 This is a geometric series which converges when x < that is when x < or < x <. Example 3 Find a power series representation for and nd its domain. + x First, we rewrite + x + x. Now, we nd a power series representation for + x, then we will multiply it by. + x can be obtained from x by x replacing x by. Since x X x n, we have: Therefore, x n + x ( ) n x n + x ( ) n x n ( ) n x n n+ x converges when jxj <, so this series converges when x < ) jxj <. So, the interval of convergence is ( ; ), the radius of convergence is. Remark 4 In the rst of these two examples, we applied the substitution to the expanded form of. In the second, we applied it to the compact form. You x can do it either way, it is simply a matter of choice. Example 5 Suppose that you are given that a series repersentation for e x is e x x n in ( ; ). What is a series representation for e x and what is its domain? We go from e x to e x using the substitution x! x. Thus e x x n x n also valid in ( ; ) 3

4 .3 Di erentiation and Integration The driving force behind the integration and di erentiation techniques is the theorem below which we state without proof. Theorem 6 If the power series c n (x R > 0 then the function de ned by f (x) a) n has a radius of convergence c n (x a) n c 0 + c (x a) + c (x a) + ::: is di erentiable (hence) continuous on (a R; a + R) and. f 0 (x) c + c (x a) + 3c 3 (x a) + ::: In other words, the series can be di erentiated term by term.. R (x a) (x a) 3 f (x) dx C + c 0 (x a) + c + c + ::: In other words, 3 the series can be integrated term by term. 3. Note that whether we di erentiate or integrate, the radius of convergence is preserved. However, convergence at the endpoints must be investigated every time. Remark 7 This theorem simply says that the sum rule for derivatives and integrals also applies to power series. Remember that a power series is a sum, but it is an in nite sums. So, in general, the results we know for nite sums do not apply to in nite sums. The theorem above says that it does in the case of in nite series. Remark 8 The formula in part of the theorem is obtained simply by di erentiating the series term by term. Since f (x) c 0 + c (x a) + c (x a) + ::: then 0 f 0 (x) c 0 + c (x a) + c (x a) + ::: (c 0 ) 0 + (c (x a)) 0 + c (x a) 0 + ::: 0 + c + c (x a) + 3c 3 (x a) + ::: () Alternatively, one can also di erentiate the general formula. Since f (x) c n (x a) n 4

5 then f 0 (x)! 0 c n (x a) n (c n (x a) n ) 0 by the theorem nc n (x a) n The rst term of this series (when n 0) is 0, thus we can start summation at n. Hence, we have f 0 (x) nc n (x a) n () n The reader should check that formulas and are identical. Remark 9 The formula in part of the theorem is obtained by integrating term by term. It can also be obtained by integrating the general formula. Since f (x) c n (x a) n then Z f (x) dx Z X c n (x a) n! dx Z (c n (x a) n ) dx by the theorem Since an antiderivative of c n (x a) n is C + c n (x a) n+, we have n + Z If we expand this, we get Z f (x) dx C + c n (x a) n+ n + f (x) dx C + c 0 (x a) + c (x a) Which is the formula which appears in the theorem. + c (x a) ::: 5

6 Example 0 Given that a power series representation for f (x) is f (x) + x + x + + ::: nd a power series representation for f 0 (x) and R f (x) dx. x n First, we nd f 0 (x). From the theorem, we know it is enough to di erentiate term by term. Thus, f 0 (x) x + 3x + ::: + x + 3x + ::: Note that we can also obtain the same result by using the general formula. In this case, f (x) x n Thus f 0 (x) Which gives us the same answer. (x n ) 0 n nx n nx n Next, we nd R f (x) dx. From the theorem, it is enough to integrate term by term. Thus since f (x) + x + x + + :::, we have: Z f (x) dx C + x + x + x3 3 + x4 4 + ::: Alternatively, we can work from the general formula. Since f (x) we have Which is the same formula. Z f (x) dx Z (x n ) dx C + x n+ n + x n, 6

7 .3. Di erentiation This time, we nd the series representation of a given series by di erentiating the power series of a known function. More precisely, if f 0 (x) g (x), and if we have a series representation for f and need one for g, we simply di erentiate the series representation of f. The theorem above tells us that the radius of convergence will be the same. However, we will have to check the endpoints. Example Find a series representation for convergence. We begin by noting that we have:, nd the interval of ( x) 0 x ( x). Since x +x+x + +::::, ( x) + x + x + + ::: 0 + x + 3x :::: nx n n The radius of convergence is still. Since converges for x in ( ; ), we x know that will also converge in ( ; ). It might also converge at the ( x) endpoints, so we need to check them. Do it as an exercise. Remark If you prefer to work from the compact form of the series, it can be done. x X x n ( x)! 0 x n (x n ) 0 n nx n However, you have to be careful with the starting value of n. Example 3 Suppose you know that a series representation for sin x is sin x x 3! + x5 5! x 7 7! + ::: ( ) n x n+ (n + )! 7

8 Find a power series representation for cos x. cos x (sin x) 0 x 3! + x5 5! x! + x4 4! ( ) n x n (n)! x 7 0 7! + ::: x 6 6! + ::: Example 4 Find a power series representation for xe x repersentation for e x is e x x n in ( ; ). We can do this problem two ways. given that a series Method Using substitution, we can nd a power series representation for e x, then multiply what we nd by x. The rst part was done earlier, x n and we found that e x on ( ; ). Thus, xe x xx n x n+ also in ( ; ). Method We note that xe x e x 0. So, using substitution, we can nd a power series representation for e x, then di erentiate it to get a series 8

9 representation for xe x. xe x e x 0 n n! 0 x n nx n nx n x n (n )! x n+ when n 0, nxn 0 So, either way, we nd the same answer..3. Integration This time we nd the power series representation of a function by integrating the power series representation of a known function. If g (x) R f (x) dx and we know a power series representation for f (x), we can get a series representation for g (x) by integrating the series representation of f. Example 5 Find a power series representation for ln ( x). We know that ln ( x) R dx. By our earlier work, we found that x x + x + x + + ::: in ( ; ), so ln ( x) C + x + x + x3 3 + ::: We also know that ln 0, From the above equation, we get that C 0 by letting x 0. Therefore ln ( x) x + x + x3 3 + ::: x n+ n + Therefore, ln ( x) x n+ n + 9

10 Since the original series converges in ( ; ), this one will also converge there. The end points should be checked, we leave it as an exercise. Example 6 Find a power series rpresentation for tan x. We use the fact that tan x R se see that dx + x. First, since x +x+x + +:::, + x x + x 4 x 6 + ::: and therefore tan x C + x 3 + x5 5 Using the fact that tan 0 0 gives us C 0. Thus tan x x.4 Things to Know 3 + x5 5 x ::: x ::: Be able to nd the series representation of a function by substitution, integration or di erentiation. Problems assigned: #, 3, 5, 7,, 3,, 35 on pages 604, 605 Taylor and Maclaurin s Series (8.7). Introduction The previous section showed us how to nd the series representation of some functions by using the series representation of known functions. The methods we studied are limited since they require us to relate the function to which we want a series representation with one for which we already know a series representation. In this section, we develop a more direct approach. When dealing with functions and their power series representation, there are three fundamental questions one has to answer:. Does a given function have a power series representation?. If it does, how do we nd it? 3. What is the domain in other words, for which values of x is the representation valid? Question is more theoretical, we won t address it. We will concentrate on questions and 3. Assuming f has a power series representation that is f (x) c 0 +c (x a)+ c (x a) + :::, we want to nd what the power series representation is, that is we need to nd the coe cients c 0 ; c ; c ; :::. It turns out that it is not very di cult. The technique used is worth remembering. We rst nd c 0. Having found c 0 we next nd c. Then, we nd c and so on. 0

11 Finding c 0. Since f (x) c 0 + c (x a) + c (x a) + c 3 (x a) 3 + c 4 (x a) 4 + ::: (3) it follows that f (a) c 0 + c (0) + c (0) + ::: c 0 Finding c. Di erentiating equation 3 gives us f 0 (x) c + c (x a) + 3c 3 (x a) + 4c 4 (x a) 3 + ::: Therefore, f 0 (a) c Finding c. We proceed the same way. First, we compute f 00 (x), then f 00 (a). Therefore or f 00 (x) c + () (3) c 3 (x a) + (3) (4) c 4 (x a) + ::: f 00 (a) c c f 00 (a) In general. Continuing this way, we can see that. De nitions and Theorems c n f (n) (a) Theorem 7 If the function f has a power series representation, that is if f (x) c n (x a) n c 0 + c (x a) + c (x a) + ::: for jx aj < R then its coe cients are given by: In other words c n f (n) (a) f (x) f (a) + f 0 (a) (x a) + f 00 (a) (x a) De nition 8. The series in the previous theorem is called the Taylor series of the function f at a. + f 000 (a) (x a)3 3! f (n) (a) + ::: (x a) n!

12 . The nth partial sum is called the nth order Taylor polynomial It is denoted T n : So, nx f (i) (a) T n (x) (x a) i i! i0 3. In the special case a 0, the series is called a Maclaurin s Series. So, a f (n) (0) Maclaurin s series is of the form x n and the Maclaurin s series for a function f is given by f (x).3 Examples f (n) (0) x n f (0) + f 0 (0) x + f 00 (0) x + f 000 (0) x3 3! + ::: We now look how to nd the Taylor and Maclaurin s series of some functions. Example 9 Find the Maclaurin s series for f (x) e x, nd its domain. f (n) (0) The series will be of the form x n, we simply need to nd the coef cients f (n) (0). This is easy. Since all the derivatives of e x are e x, it follows that f (n (x) e x, thus f (n) (0) e 0, hence e x f (n) (0) x n x n To nd where this series converges, we use the ration test and compute: lim a n+ a n lim Thus the domain is all real numbers. x n+ (n + )! x n jxj n+ lim (n + )! jxj n jxj lim n + 0

13 Example 0 Find a Taylor series for f (x) e x centered at. f (n) () The series will be of the form (x ) n, we simply need to nd the coe cients f (n) (). This is easy. Since all the derivatives of e x are e x, it follows that f (n (x) e x, thus f (n) () e, hence e x f (n) () e (x )n (x ) n Example Find the n th order Taylor polynomial for e x centered at 0 and centered at. Plot these polynomials for n ; ; 3; 4; 5. What do you notice? We already computed the power series corresponding to these two situations. We found that and e x + x + x! + x3 3! + x4 4! + x5 5! + x6 6! + ::: e x e + e (x ) (x )3 (x ) + e + e + :::! 3! e + (x ) + (x )! + (x )3 3! + (x )4 4! + (x )5 5! + :::! If we denote T n the n th order Taylor polynomial for e x centered at 0 and Q n the n th order Taylor polynomial for e x centered at, we have: n th order Taylor polynomials for e x centered at 0. T (x) + x T (x) + x + x! T 3 (x) + x + x! + x3 3! T 4 (x) + x + x! + x3 3! + x4 4! T 5 (x) + x + x! + x3 3! + x4 4! + x5 5! The graphs is shown on the next page. 3

14 Graphs of e x and the rst 5 Taylor polynomials centered at 0. The functions have the following colors: e x : black T : blue T : red T 3 : green T 4 : purple T 5 : yellow 4

15 n th order Taylor polynomial for e x centered at : Q (x) e ( + (x )) Q (x) e + (x ) + Q 3 (x) e + (x ) + Q 4 (x) e + (x ) + Q 5 (x) e + (x ) +! (x )! (x )! (x )! (x )! The graphs are shown on the next page ! (x )3 3! (x )3 3! (x )3 3! + +! (x )4 4! (x )4 4! +! (x )5 5! 5

16 Graphs of e x and the rst 5 Taylor polynomials centered at. The functions have the following colors: e x : black Q : blue Q : red Q 3 : green Q 4 : purple Q 5 : yellow We can see the following: The Taylor polynomial approximates the functions well near the point at which the series is centered. As we move away from this point, the approximation deteriorates very quickly. The approximation is better the higher the degree of the Taylor polynomial. More speci cally, the Taylor polynomial stay closer to the function over a larger interval, the higher its degree. 6

17 Example Find a Maclaurin s series for f (x) sin x and nd its domain f (n) (0) The series will be of the form x n, we simply need to nd the coe - cients f (n) (0). That is we need to nd all the derivatives of sin x and evaluate them at x 0. We summarize our ndings in the table below: n f (n) (x) f (n) (0) 0 sin x 0 cos x sin x 0 3 cos x 4 sin x 0 So, we see that we will have coe cients only for odd values of n. In addition, the sign of the coe cients will alternate. Thus, since we have f (x) f (0) + f 0 (0) x + f 00 (0) x + f 000 (0) x3 3! + f (4) (0) x4 4! + ::: sin x 0 + x + 0 x 3! + x5 5! 3! x5 5! x 7 7! + ::: ( ) n x n+ (n + )! To nd where this series converges, we use the ration test and compute lim a n+ a n. Since a n xn+ (n + )!, a n+ xn+3 (n + 3)!. Therefore, x n+3 lim a n+ a n lim (n + 3)! x n+ (n + )! jxj n+3 (n + )! lim jxj n+ (n + 3)! jxj lim (n + )! (n + 3)! ::: jxj lim (n + ) (n + 3) 0 Thus the series representation is valid for all x. 7

18 Here are some important functions and their corresponding Maclaurin s series x + x + x + + x 4 + ::: ( ; ) e x + x + x! + x3 + ::: ( ; ) 3! sin x x cos x tan x x 3! + x5 5! x! + x4 4! 3 + x5 5 x 7 7! x 6 + ::: ( ; ) + ::: 6! ( ; ) x 7 + ::: 7 [ ; ] Remark 3 The n th order Taylor polynomial (T n ) associated with the series expansion of a function f is the n th degree polynomial obtained by truncating the series expansion and keeping only the terms of degree less than or equal to n. In the case of sin x, since It follows that and so on. sin x x 3! + x5 5! T x T x T 3 x T 4 x T 5 x T 6 x 3! 3! 3! + x5 5! 3! + x5 5! x 7 7! + :::.4 Summary We now have four di erent techniques to nd a series representation for a function. These techniques are:. Substitution. Di erentiation 3. Integration 8

19 4. Taylor/Maclaurin s series. It may appear that the last technique is much more powerful, as it gives us a direct way to derive the series representation. In contrast, the rst three techniques require we start from a known series representation. However, the rst three techniques should not be ignored. In many cases, they make the work easier. We illustrate this with a few examples. Example 4 Find a Maclaurin s series for f (x) e x. Of course, this can be done directly. But consider the problem of nding all the derivative of e x. One can also start from e x and substitute x for x. Since it follows that e x x n + x + x + x3 3! + x4 4! e x x n ( ) n x n This was pretty painless. To convince yourself that this is the way to do it, try the direct approach instead! Example 5 Find a Maclaurin s series for cos x. Again, one can try the direct approach as in example. It is not too di cult. One can also realize that (sin x) 0 cos x. Thus, one can start with the series for sin x (which we already derived) and nd the series for cos x by di erentiating it. We get cos x (sin x) 0 ( ) n x n+ (n + )! ( ) n x n+ ( ) n x n (n)! x + x4 4! (n + )! x 6 6!! 0 0 9

20 .5 Things to Remember Given a function, be able to nd its Taylor or Maclaurin s series. Be able to nd the radius and interval of convergence of Taylor or Maclaurin s series. Section 8.7: # 3, 5, 7, 9,, 3, 9,, 3, 5, 3 on pages 65, Applications The purpose of this section is to show the reader how Taylor series can be used to approximate functions. The approximation can then be used to either evaluate a function at speci c values of x, to integrate or to di erentiate the function. Of course, we would only use this technique with functions for which the traditional calculus methods do not work. For example, we may need to compute Z 0 e x dx. This cannot be done using the integration techniques learned in a traditional calculus class since e x does not have an antiderivative which can be expressed in terms of elementary functions. Another application might be to approximate sin (0:0), without a calculator. The di culty does not lie in the series representation of a given function, we now know how to represent functions as power series. However, series have in nitely many terms, for practical purposes, we can only use a nite number of them. Thus, we replace the in - nite series by the corresponding Taylor polynomial (see de nition 8) of order n (T n ), for some n. We then use the Taylor polynomial instead of the function. This can be used to evaluate a function, integrate a function or di erentiate a function. However, when we perform the following approximation f (x) f (a) + f 0 (a) (x a) + f 00 (a)! (x a) + ::: + f (n) (a) there are several questions to answer before we can carry it out: (x a) n. How do we pick a, the number around which the series is centered?. How do we pick n so the Taylor polynomial T n approximates the given function f within the desired accuracy? Answer to question There are several factors to take under consideration. First, since we have to evaluate f (n) (a), a must be picked so we can do this evaluation easily. Second, you will recall that the accuracy of the approximation decreases as x gets further away from a. Therefore, we need to pick a so that the values at which f (x) will be approximated are in the domain of the series, and not too far from a. For example, if we had to approximate sin (:00), then a 0 would be a good choice because it satis es both criteria. 0

21 Answer to question Once we have selected a and have a series representation for f, we use the techniques studied to approximate a series and nd the error. The examples below illustrate these applications. Example 6 Find the nth order Taylor polynomial for f (x) cos x when n ; 3; 4; 5; 6. Sketch the graph of cos x as well as the Taylor polynomials found. We already know the power series for cos x. So, cos x P (x) P 3 (x) P 4 (x) P 5 (x) P 6 (x) x! + x4 4! x! x! x! + x4 4! x! + x4 4! x! + x4 4! x 6 6! + x8 8! :::: You will note that because every other coe cient in the series expansion of cos x is 0; P 3 P, P 5 P 4. The graph of these polynomials is shown on gure. Remark 7 You will notice that as n increases, P n gets closer to the graph of cos x. In other words, the accuracy of our approximation increases with n. However, P n is a good approximation for cos x in a neighborhood of 0, as we move away from 0, P n gets further and further away from cos x. This is important. When one approximates a function with a Taylor polynomial about a, the approximation is good only for values of x close to a. Example 8 Approximate cos 0:0 with an error less than 0 0. First, we note that since :0 is close to 0, we can use a Taylor polynomial centered at 0 to approximate cos (:0). Therefore, using the Taylor polynomial for cos x centered at 0, and replacing x by 0:0, we get: cos 0:0 nx i0 ( ) i 0:0 i (i)! We need to nd n so that if we approximate ( ) i 0:0 i nx by ( ) i 0:0 i (i)! (i)!, i0 i0 the error is less than 0 0. We notice that ( ) i 0:0 i is an alternating (i)! i0 x 6 6!

22 Figure : Graph of cos x and some Taylor polynomials series with b n 0:0n, so we know how to estimate its error. The error is (n)! always less than b n+. So, if we want the error to be less than 0 0, it is enough to solve: 0:0 (n+) (n + )! b n+ < 0 0 < 0 0 We solve this by trying various values of n. The table below shows this procedure:

23 0:0 (n+) n (n + )! We see that n 3 is enough. Therefore: cos 0:0 3X ( ) n 0:0 n (n)! 0: Example 9 Approximate R 0 e x dx with an error less than 0:00. First, we nd a series representation for e x. Since e x x n it follows that Therefore and therefore Z 0 Z e x e x dx e x dx ( ) n x n ( ) n x n+ (n + ) ( ) n x n+ (n + ) 0 ( ) n (n + ) This is an alternating series ( ) n b n with b n. From our (n + ) knowledge of alternating series, we know that if we approximate ( ) i (i + ) i! i0 nx by ( ) i (i + ) i!, the error will be less than b n+ (n + 3) (n + )!. So, i0 we nd n such that (n + 3) (n + )! < :00 3

24 We try several values of n, we nd that when n 3, and when n 4, : So, (n + 3) (n + )! 4X gives us the desired approximation. ( ) n 0: (n + ) (n + 3) (n + )! : Problems The problems assigned for power series, Taylor series and representation of functions as power series were: Section 8.6: #, 3, 5, 7,, 3,, 35 on pages 60, 6. Section 8.7: # 3, 5, 7, 9,, 3, 9,, 3, 5, 3 on pages 65, 66. In addition, for the applications discussed in this section, do # 3, 5, 7 on page 68. 4

36 CHAPTER 1. LIMITS AND CONTINUITY. Figure 1.17: At which points is f not continuous?

36 CHAPTER 1. LIMITS AND CONTINUITY. Figure 1.17: At which points is f not continuous? 36 CHAPTER 1. LIMITS AND CONTINUITY 1.3 Continuity Before Calculus became clearly de ned, continuity meant that one could draw the graph of a function without having to lift the pen and pencil. While this

More information

Partial Fractions Decomposition

Partial Fractions Decomposition Partial Fractions Decomposition Dr. Philippe B. Laval Kennesaw State University August 6, 008 Abstract This handout describes partial fractions decomposition and how it can be used when integrating rational

More information

Taylor and Maclaurin Series

Taylor and Maclaurin Series Taylor and Maclaurin Series In the preceding section we were able to find power series representations for a certain restricted class of functions. Here we investigate more general problems: Which functions

More information

Sample Problems. Practice Problems

Sample Problems. Practice Problems Lecture Notes Partial Fractions page Sample Problems Compute each of the following integrals.. x dx. x + x (x + ) (x ) (x ) dx 8. x x dx... x (x + ) (x + ) dx x + x x dx x + x x + 6x x dx + x 6. 7. x (x

More information

1.2 Solving a System of Linear Equations

1.2 Solving a System of Linear Equations 1.. SOLVING A SYSTEM OF LINEAR EQUATIONS 1. Solving a System of Linear Equations 1..1 Simple Systems - Basic De nitions As noticed above, the general form of a linear system of m equations in n variables

More information

1 Lecture: Integration of rational functions by decomposition

1 Lecture: Integration of rational functions by decomposition Lecture: Integration of rational functions by decomposition into partial fractions Recognize and integrate basic rational functions, except when the denominator is a power of an irreducible quadratic.

More information

160 CHAPTER 4. VECTOR SPACES

160 CHAPTER 4. VECTOR SPACES 160 CHAPTER 4. VECTOR SPACES 4. Rank and Nullity In this section, we look at relationships between the row space, column space, null space of a matrix and its transpose. We will derive fundamental results

More information

c 2008 Je rey A. Miron We have described the constraints that a consumer faces, i.e., discussed the budget constraint.

c 2008 Je rey A. Miron We have described the constraints that a consumer faces, i.e., discussed the budget constraint. Lecture 2b: Utility c 2008 Je rey A. Miron Outline: 1. Introduction 2. Utility: A De nition 3. Monotonic Transformations 4. Cardinal Utility 5. Constructing a Utility Function 6. Examples of Utility Functions

More information

Lectures 5-6: Taylor Series

Lectures 5-6: Taylor Series Math 1d Instructor: Padraic Bartlett Lectures 5-: Taylor Series Weeks 5- Caltech 213 1 Taylor Polynomials and Series As we saw in week 4, power series are remarkably nice objects to work with. In particular,

More information

A power series about x = a is the series of the form

A power series about x = a is the series of the form POWER SERIES AND THE USES OF POWER SERIES Elizabeth Wood Now we are finally going to start working with a topic that uses all of the information from the previous topics. The topic that we are going to

More information

The Method of Partial Fractions Math 121 Calculus II Spring 2015

The Method of Partial Fractions Math 121 Calculus II Spring 2015 Rational functions. as The Method of Partial Fractions Math 11 Calculus II Spring 015 Recall that a rational function is a quotient of two polynomials such f(x) g(x) = 3x5 + x 3 + 16x x 60. The method

More information

Sequences and Series

Sequences and Series Sequences and Series Consider the following sum: 2 + 4 + 8 + 6 + + 2 i + The dots at the end indicate that the sum goes on forever. Does this make sense? Can we assign a numerical value to an infinite

More information

MATH 132: CALCULUS II SYLLABUS

MATH 132: CALCULUS II SYLLABUS MATH 32: CALCULUS II SYLLABUS Prerequisites: Successful completion of Math 3 (or its equivalent elsewhere). Math 27 is normally not a sufficient prerequisite for Math 32. Required Text: Calculus: Early

More information

1.7 Graphs of Functions

1.7 Graphs of Functions 64 Relations and Functions 1.7 Graphs of Functions In Section 1.4 we defined a function as a special type of relation; one in which each x-coordinate was matched with only one y-coordinate. We spent most

More information

Lies My Calculator and Computer Told Me

Lies My Calculator and Computer Told Me Lies My Calculator and Computer Told Me 2 LIES MY CALCULATOR AND COMPUTER TOLD ME Lies My Calculator and Computer Told Me See Section.4 for a discussion of graphing calculators and computers with graphing

More information

CAPM, Arbitrage, and Linear Factor Models

CAPM, Arbitrage, and Linear Factor Models CAPM, Arbitrage, and Linear Factor Models CAPM, Arbitrage, Linear Factor Models 1/ 41 Introduction We now assume all investors actually choose mean-variance e cient portfolios. By equating these investors

More information

Microeconomic Theory: Basic Math Concepts

Microeconomic Theory: Basic Math Concepts Microeconomic Theory: Basic Math Concepts Matt Van Essen University of Alabama Van Essen (U of A) Basic Math Concepts 1 / 66 Basic Math Concepts In this lecture we will review some basic mathematical concepts

More information

1 Another method of estimation: least squares

1 Another method of estimation: least squares 1 Another method of estimation: least squares erm: -estim.tex, Dec8, 009: 6 p.m. (draft - typos/writos likely exist) Corrections, comments, suggestions welcome. 1.1 Least squares in general Assume Y i

More information

Partial Derivatives. @x f (x; y) = @ x f (x; y) @x x2 y + @ @x y2 and then we evaluate the derivative as if y is a constant.

Partial Derivatives. @x f (x; y) = @ x f (x; y) @x x2 y + @ @x y2 and then we evaluate the derivative as if y is a constant. Partial Derivatives Partial Derivatives Just as derivatives can be used to eplore the properties of functions of 1 variable, so also derivatives can be used to eplore functions of 2 variables. In this

More information

LIES MY CALCULATOR AND COMPUTER TOLD ME

LIES MY CALCULATOR AND COMPUTER TOLD ME LIES MY CALCULATOR AND COMPUTER TOLD ME See Section Appendix.4 G for a discussion of graphing calculators and computers with graphing software. A wide variety of pocket-size calculating devices are currently

More information

3 Contour integrals and Cauchy s Theorem

3 Contour integrals and Cauchy s Theorem 3 ontour integrals and auchy s Theorem 3. Line integrals of complex functions Our goal here will be to discuss integration of complex functions = u + iv, with particular regard to analytic functions. Of

More information

Estimating the Average Value of a Function

Estimating the Average Value of a Function Estimating the Average Value of a Function Problem: Determine the average value of the function f(x) over the interval [a, b]. Strategy: Choose sample points a = x 0 < x 1 < x 2 < < x n 1 < x n = b and

More information

1 Error in Euler s Method

1 Error in Euler s Method 1 Error in Euler s Method Experience with Euler s 1 method raises some interesting questions about numerical approximations for the solutions of differential equations. 1. What determines the amount of

More information

Polynomials. Dr. philippe B. laval Kennesaw State University. April 3, 2005

Polynomials. Dr. philippe B. laval Kennesaw State University. April 3, 2005 Polynomials Dr. philippe B. laval Kennesaw State University April 3, 2005 Abstract Handout on polynomials. The following topics are covered: Polynomial Functions End behavior Extrema Polynomial Division

More information

Section 4.4. Using the Fundamental Theorem. Difference Equations to Differential Equations

Section 4.4. Using the Fundamental Theorem. Difference Equations to Differential Equations Difference Equations to Differential Equations Section 4.4 Using the Fundamental Theorem As we saw in Section 4.3, using the Fundamental Theorem of Integral Calculus reduces the problem of evaluating a

More information

2.2 Derivative as a Function

2.2 Derivative as a Function 2.2 Derivative as a Function Recall that we defined the derivative as f (a) = lim h 0 f(a + h) f(a) h But since a is really just an arbitrary number that represents an x-value, why don t we just use x

More information

10.2 Series and Convergence

10.2 Series and Convergence 10.2 Series and Convergence Write sums using sigma notation Find the partial sums of series and determine convergence or divergence of infinite series Find the N th partial sums of geometric series and

More information

Advanced Microeconomics

Advanced Microeconomics Advanced Microeconomics Ordinal preference theory Harald Wiese University of Leipzig Harald Wiese (University of Leipzig) Advanced Microeconomics 1 / 68 Part A. Basic decision and preference theory 1 Decisions

More information

5.1 Radical Notation and Rational Exponents

5.1 Radical Notation and Rational Exponents Section 5.1 Radical Notation and Rational Exponents 1 5.1 Radical Notation and Rational Exponents We now review how exponents can be used to describe not only powers (such as 5 2 and 2 3 ), but also roots

More information

Name: ID: Discussion Section:

Name: ID: Discussion Section: Math 28 Midterm 3 Spring 2009 Name: ID: Discussion Section: This exam consists of 6 questions: 4 multiple choice questions worth 5 points each 2 hand-graded questions worth a total of 30 points. INSTRUCTIONS:

More information

POLYNOMIAL FUNCTIONS

POLYNOMIAL FUNCTIONS POLYNOMIAL FUNCTIONS Polynomial Division.. 314 The Rational Zero Test.....317 Descarte s Rule of Signs... 319 The Remainder Theorem.....31 Finding all Zeros of a Polynomial Function.......33 Writing a

More information

1 if 1 x 0 1 if 0 x 1

1 if 1 x 0 1 if 0 x 1 Chapter 3 Continuity In this chapter we begin by defining the fundamental notion of continuity for real valued functions of a single real variable. When trying to decide whether a given function is or

More information

Lecture 1: Systems of Linear Equations

Lecture 1: Systems of Linear Equations MTH Elementary Matrix Algebra Professor Chao Huang Department of Mathematics and Statistics Wright State University Lecture 1 Systems of Linear Equations ² Systems of two linear equations with two variables

More information

Stanford Math Circle: Sunday, May 9, 2010 Square-Triangular Numbers, Pell s Equation, and Continued Fractions

Stanford Math Circle: Sunday, May 9, 2010 Square-Triangular Numbers, Pell s Equation, and Continued Fractions Stanford Math Circle: Sunday, May 9, 00 Square-Triangular Numbers, Pell s Equation, and Continued Fractions Recall that triangular numbers are numbers of the form T m = numbers that can be arranged in

More information

88 CHAPTER 2. VECTOR FUNCTIONS. . First, we need to compute T (s). a By definition, r (s) T (s) = 1 a sin s a. sin s a, cos s a

88 CHAPTER 2. VECTOR FUNCTIONS. . First, we need to compute T (s). a By definition, r (s) T (s) = 1 a sin s a. sin s a, cos s a 88 CHAPTER. VECTOR FUNCTIONS.4 Curvature.4.1 Definitions and Examples The notion of curvature measures how sharply a curve bends. We would expect the curvature to be 0 for a straight line, to be very small

More information

This means there are two equilibrium solutions 0 and K. dx = rx(1 x). x(1 x) dt = r

This means there are two equilibrium solutions 0 and K. dx = rx(1 x). x(1 x) dt = r Verhulst Model For Population Growth The first model (t) = r is not that realistic as it either led to a population eplosion or to etinction. This simple model was improved on by building into this differential

More information

PYTHAGOREAN TRIPLES KEITH CONRAD

PYTHAGOREAN TRIPLES KEITH CONRAD PYTHAGOREAN TRIPLES KEITH CONRAD 1. Introduction A Pythagorean triple is a triple of positive integers (a, b, c) where a + b = c. Examples include (3, 4, 5), (5, 1, 13), and (8, 15, 17). Below is an ancient

More information

3. Mathematical Induction

3. Mathematical Induction 3. MATHEMATICAL INDUCTION 83 3. Mathematical Induction 3.1. First Principle of Mathematical Induction. Let P (n) be a predicate with domain of discourse (over) the natural numbers N = {0, 1,,...}. If (1)

More information

Differentiation and Integration

Differentiation and Integration This material is a supplement to Appendix G of Stewart. You should read the appendix, except the last section on complex exponentials, before this material. Differentiation and Integration Suppose we have

More information

MA107 Precalculus Algebra Exam 2 Review Solutions

MA107 Precalculus Algebra Exam 2 Review Solutions MA107 Precalculus Algebra Exam 2 Review Solutions February 24, 2008 1. The following demand equation models the number of units sold, x, of a product as a function of price, p. x = 4p + 200 a. Please write

More information

14.451 Lecture Notes 10

14.451 Lecture Notes 10 14.451 Lecture Notes 1 Guido Lorenzoni Fall 29 1 Continuous time: nite horizon Time goes from to T. Instantaneous payo : f (t; x (t) ; y (t)) ; (the time dependence includes discounting), where x (t) 2

More information

4.5 Linear Dependence and Linear Independence

4.5 Linear Dependence and Linear Independence 4.5 Linear Dependence and Linear Independence 267 32. {v 1, v 2 }, where v 1, v 2 are collinear vectors in R 3. 33. Prove that if S and S are subsets of a vector space V such that S is a subset of S, then

More information

Partial Fractions. p(x) q(x)

Partial Fractions. p(x) q(x) Partial Fractions Introduction to Partial Fractions Given a rational function of the form p(x) q(x) where the degree of p(x) is less than the degree of q(x), the method of partial fractions seeks to break

More information

COMP 250 Fall 2012 lecture 2 binary representations Sept. 11, 2012

COMP 250 Fall 2012 lecture 2 binary representations Sept. 11, 2012 Binary numbers The reason humans represent numbers using decimal (the ten digits from 0,1,... 9) is that we have ten fingers. There is no other reason than that. There is nothing special otherwise about

More information

MA4001 Engineering Mathematics 1 Lecture 10 Limits and Continuity

MA4001 Engineering Mathematics 1 Lecture 10 Limits and Continuity MA4001 Engineering Mathematics 1 Lecture 10 Limits and Dr. Sarah Mitchell Autumn 2014 Infinite limits If f(x) grows arbitrarily large as x a we say that f(x) has an infinite limit. Example: f(x) = 1 x

More information

4.3 Lagrange Approximation

4.3 Lagrange Approximation 206 CHAP. 4 INTERPOLATION AND POLYNOMIAL APPROXIMATION Lagrange Polynomial Approximation 4.3 Lagrange Approximation Interpolation means to estimate a missing function value by taking a weighted average

More information

Inner Product Spaces

Inner Product Spaces Math 571 Inner Product Spaces 1. Preliminaries An inner product space is a vector space V along with a function, called an inner product which associates each pair of vectors u, v with a scalar u, v, and

More information

G. GRAPHING FUNCTIONS

G. GRAPHING FUNCTIONS G. GRAPHING FUNCTIONS To get a quick insight int o how the graph of a function looks, it is very helpful to know how certain simple operations on the graph are related to the way the function epression

More information

An important theme in this book is to give constructive definitions of mathematical objects. Thus, for instance, if you needed to evaluate.

An important theme in this book is to give constructive definitions of mathematical objects. Thus, for instance, if you needed to evaluate. Chapter 10 Series and Approximations An important theme in this book is to give constructive definitions of mathematical objects. Thus, for instance, if you needed to evaluate 1 0 e x2 dx, you could set

More information

Continued Fractions and the Euclidean Algorithm

Continued Fractions and the Euclidean Algorithm Continued Fractions and the Euclidean Algorithm Lecture notes prepared for MATH 326, Spring 997 Department of Mathematics and Statistics University at Albany William F Hammond Table of Contents Introduction

More information

Notes on metric spaces

Notes on metric spaces Notes on metric spaces 1 Introduction The purpose of these notes is to quickly review some of the basic concepts from Real Analysis, Metric Spaces and some related results that will be used in this course.

More information

1 Present and Future Value

1 Present and Future Value Lecture 8: Asset Markets c 2009 Je rey A. Miron Outline:. Present and Future Value 2. Bonds 3. Taxes 4. Applications Present and Future Value In the discussion of the two-period model with borrowing and

More information

Math 1B, lecture 5: area and volume

Math 1B, lecture 5: area and volume Math B, lecture 5: area and volume Nathan Pflueger 6 September 2 Introduction This lecture and the next will be concerned with the computation of areas of regions in the plane, and volumes of regions in

More information

Section 2.4: Equations of Lines and Planes

Section 2.4: Equations of Lines and Planes Section.4: Equations of Lines and Planes An equation of three variable F (x, y, z) 0 is called an equation of a surface S if For instance, (x 1, y 1, z 1 ) S if and only if F (x 1, y 1, z 1 ) 0. x + y

More information

Series FOURIER SERIES. Graham S McDonald. A self-contained Tutorial Module for learning the technique of Fourier series analysis

Series FOURIER SERIES. Graham S McDonald. A self-contained Tutorial Module for learning the technique of Fourier series analysis Series FOURIER SERIES Graham S McDonald A self-contained Tutorial Module for learning the technique of Fourier series analysis Table of contents Begin Tutorial c 004 g.s.mcdonald@salford.ac.uk 1. Theory.

More information

Algebra. Exponents. Absolute Value. Simplify each of the following as much as possible. 2x y x + y y. xxx 3. x x x xx x. 1. Evaluate 5 and 123

Algebra. Exponents. Absolute Value. Simplify each of the following as much as possible. 2x y x + y y. xxx 3. x x x xx x. 1. Evaluate 5 and 123 Algebra Eponents Simplify each of the following as much as possible. 1 4 9 4 y + y y. 1 5. 1 5 4. y + y 4 5 6 5. + 1 4 9 10 1 7 9 0 Absolute Value Evaluate 5 and 1. Eliminate the absolute value bars from

More information

Common sense, and the model that we have used, suggest that an increase in p means a decrease in demand, but this is not the only possibility.

Common sense, and the model that we have used, suggest that an increase in p means a decrease in demand, but this is not the only possibility. Lecture 6: Income and Substitution E ects c 2009 Je rey A. Miron Outline 1. Introduction 2. The Substitution E ect 3. The Income E ect 4. The Sign of the Substitution E ect 5. The Total Change in Demand

More information

Mathematics Pre-Test Sample Questions A. { 11, 7} B. { 7,0,7} C. { 7, 7} D. { 11, 11}

Mathematics Pre-Test Sample Questions A. { 11, 7} B. { 7,0,7} C. { 7, 7} D. { 11, 11} Mathematics Pre-Test Sample Questions 1. Which of the following sets is closed under division? I. {½, 1,, 4} II. {-1, 1} III. {-1, 0, 1} A. I only B. II only C. III only D. I and II. Which of the following

More information

Solutions to Homework 10

Solutions to Homework 10 Solutions to Homework 1 Section 7., exercise # 1 (b,d): (b) Compute the value of R f dv, where f(x, y) = y/x and R = [1, 3] [, 4]. Solution: Since f is continuous over R, f is integrable over R. Let x

More information

Undergraduate Notes in Mathematics. Arkansas Tech University Department of Mathematics

Undergraduate Notes in Mathematics. Arkansas Tech University Department of Mathematics Undergraduate Notes in Mathematics Arkansas Tech University Department of Mathematics An Introductory Single Variable Real Analysis: A Learning Approach through Problem Solving Marcel B. Finan c All Rights

More information

HOMEWORK 5 SOLUTIONS. n!f n (1) lim. ln x n! + xn x. 1 = G n 1 (x). (2) k + 1 n. (n 1)!

HOMEWORK 5 SOLUTIONS. n!f n (1) lim. ln x n! + xn x. 1 = G n 1 (x). (2) k + 1 n. (n 1)! Math 7 Fall 205 HOMEWORK 5 SOLUTIONS Problem. 2008 B2 Let F 0 x = ln x. For n 0 and x > 0, let F n+ x = 0 F ntdt. Evaluate n!f n lim n ln n. By directly computing F n x for small n s, we obtain the following

More information

The Binomial Distribution

The Binomial Distribution The Binomial Distribution James H. Steiger November 10, 00 1 Topics for this Module 1. The Binomial Process. The Binomial Random Variable. The Binomial Distribution (a) Computing the Binomial pdf (b) Computing

More information

Linear and quadratic Taylor polynomials for functions of several variables.

Linear and quadratic Taylor polynomials for functions of several variables. ams/econ 11b supplementary notes ucsc Linear quadratic Taylor polynomials for functions of several variables. c 010, Yonatan Katznelson Finding the extreme (minimum or maximum) values of a function, is

More information

Partial Fractions. (x 1)(x 2 + 1)

Partial Fractions. (x 1)(x 2 + 1) Partial Fractions Adding rational functions involves finding a common denominator, rewriting each fraction so that it has that denominator, then adding. For example, 3x x 1 3x(x 1) (x + 1)(x 1) + 1(x +

More information

Stirling s formula, n-spheres and the Gamma Function

Stirling s formula, n-spheres and the Gamma Function Stirling s formula, n-spheres and the Gamma Function We start by noticing that and hence x n e x dx lim a 1 ( 1 n n a n n! e ax dx lim a 1 ( 1 n n a n a 1 x n e x dx (1 Let us make a remark in passing.

More information

5 Numerical Differentiation

5 Numerical Differentiation D. Levy 5 Numerical Differentiation 5. Basic Concepts This chapter deals with numerical approximations of derivatives. The first questions that comes up to mind is: why do we need to approximate derivatives

More information

DIFFERENTIABILITY OF COMPLEX FUNCTIONS. Contents

DIFFERENTIABILITY OF COMPLEX FUNCTIONS. Contents DIFFERENTIABILITY OF COMPLEX FUNCTIONS Contents 1. Limit definition of a derivative 1 2. Holomorphic functions, the Cauchy-Riemann equations 3 3. Differentiability of real functions 5 4. A sufficient condition

More information

Basic Proof Techniques

Basic Proof Techniques Basic Proof Techniques David Ferry dsf43@truman.edu September 13, 010 1 Four Fundamental Proof Techniques When one wishes to prove the statement P Q there are four fundamental approaches. This document

More information

Integration by Substitution

Integration by Substitution Integrtion by Substitution Dr. Philippe B. Lvl Kennesw Stte University August, 8 Abstrct This hndout contins mteril on very importnt integrtion method clled integrtion by substitution. Substitution is

More information

Chapter 31 out of 37 from Discrete Mathematics for Neophytes: Number Theory, Probability, Algorithms, and Other Stuff by J. M.

Chapter 31 out of 37 from Discrete Mathematics for Neophytes: Number Theory, Probability, Algorithms, and Other Stuff by J. M. 31 Geometric Series Motivation (I hope) Geometric series are a basic artifact of algebra that everyone should know. 1 I am teaching them here because they come up remarkably often with Markov chains. The

More information

Review of Fundamental Mathematics

Review of Fundamental Mathematics Review of Fundamental Mathematics As explained in the Preface and in Chapter 1 of your textbook, managerial economics applies microeconomic theory to business decision making. The decision-making tools

More information

Integrals of Rational Functions

Integrals of Rational Functions Integrals of Rational Functions Scott R. Fulton Overview A rational function has the form where p and q are polynomials. For example, r(x) = p(x) q(x) f(x) = x2 3 x 4 + 3, g(t) = t6 + 4t 2 3, 7t 5 + 3t

More information

Trigonometric Functions and Triangles

Trigonometric Functions and Triangles Trigonometric Functions and Triangles Dr. Philippe B. Laval Kennesaw STate University August 27, 2010 Abstract This handout defines the trigonometric function of angles and discusses the relationship between

More information

About the Gamma Function

About the Gamma Function About the Gamma Function Notes for Honors Calculus II, Originally Prepared in Spring 995 Basic Facts about the Gamma Function The Gamma function is defined by the improper integral Γ) = The integral is

More information

Limits and Continuity

Limits and Continuity Math 20C Multivariable Calculus Lecture Limits and Continuity Slide Review of Limit. Side limits and squeeze theorem. Continuous functions of 2,3 variables. Review: Limits Slide 2 Definition Given a function

More information

Week 13 Trigonometric Form of Complex Numbers

Week 13 Trigonometric Form of Complex Numbers Week Trigonometric Form of Complex Numbers Overview In this week of the course, which is the last week if you are not going to take calculus, we will look at how Trigonometry can sometimes help in working

More information

Polynomial and Rational Functions

Polynomial and Rational Functions Polynomial and Rational Functions Quadratic Functions Overview of Objectives, students should be able to: 1. Recognize the characteristics of parabolas. 2. Find the intercepts a. x intercepts by solving

More information

TOPIC 4: DERIVATIVES

TOPIC 4: DERIVATIVES TOPIC 4: DERIVATIVES 1. The derivative of a function. Differentiation rules 1.1. The slope of a curve. The slope of a curve at a point P is a measure of the steepness of the curve. If Q is a point on the

More information

I. Pointwise convergence

I. Pointwise convergence MATH 40 - NOTES Sequences of functions Pointwise and Uniform Convergence Fall 2005 Previously, we have studied sequences of real numbers. Now we discuss the topic of sequences of real valued functions.

More information

The Derivative. Philippe B. Laval Kennesaw State University

The Derivative. Philippe B. Laval Kennesaw State University The Derivative Philippe B. Laval Kennesaw State University Abstract This handout is a summary of the material students should know regarding the definition and computation of the derivative 1 Definition

More information

COMPLEX NUMBERS. a bi c di a c b d i. a bi c di a c b d i For instance, 1 i 4 7i 1 4 1 7 i 5 6i

COMPLEX NUMBERS. a bi c di a c b d i. a bi c di a c b d i For instance, 1 i 4 7i 1 4 1 7 i 5 6i COMPLEX NUMBERS _4+i _-i FIGURE Complex numbers as points in the Arg plane i _i +i -i A complex number can be represented by an expression of the form a bi, where a b are real numbers i is a symbol with

More information

Domain of a Composition

Domain of a Composition Domain of a Composition Definition Given the function f and g, the composition of f with g is a function defined as (f g)() f(g()). The domain of f g is the set of all real numbers in the domain of g such

More information

MATH 4330/5330, Fourier Analysis Section 11, The Discrete Fourier Transform

MATH 4330/5330, Fourier Analysis Section 11, The Discrete Fourier Transform MATH 433/533, Fourier Analysis Section 11, The Discrete Fourier Transform Now, instead of considering functions defined on a continuous domain, like the interval [, 1) or the whole real line R, we wish

More information

correct-choice plot f(x) and draw an approximate tangent line at x = a and use geometry to estimate its slope comment The choices were:

correct-choice plot f(x) and draw an approximate tangent line at x = a and use geometry to estimate its slope comment The choices were: Topic 1 2.1 mode MultipleSelection text How can we approximate the slope of the tangent line to f(x) at a point x = a? This is a Multiple selection question, so you need to check all of the answers that

More information

The Point-Slope Form

The Point-Slope Form 7. The Point-Slope Form 7. OBJECTIVES 1. Given a point and a slope, find the graph of a line. Given a point and the slope, find the equation of a line. Given two points, find the equation of a line y Slope

More information

Recognizing Types of First Order Differential Equations E. L. Lady

Recognizing Types of First Order Differential Equations E. L. Lady Recognizing Types of First Order Differential Equations E. L. Lady Every first order differential equation to be considered here can be written can be written in the form P (x, y)+q(x, y)y =0. This means

More information

Geometry Notes RIGHT TRIANGLE TRIGONOMETRY

Geometry Notes RIGHT TRIANGLE TRIGONOMETRY Right Triangle Trigonometry Page 1 of 15 RIGHT TRIANGLE TRIGONOMETRY Objectives: After completing this section, you should be able to do the following: Calculate the lengths of sides and angles of a right

More information

a cos x + b sin x = R cos(x α)

a cos x + b sin x = R cos(x α) a cos x + b sin x = R cos(x α) In this unit we explore how the sum of two trigonometric functions, e.g. cos x + 4 sin x, can be expressed as a single trigonometric function. Having the ability to do this

More information

The Mean Value Theorem

The Mean Value Theorem The Mean Value Theorem THEOREM (The Extreme Value Theorem): If f is continuous on a closed interval [a, b], then f attains an absolute maximum value f(c) and an absolute minimum value f(d) at some numbers

More information

Exact Nonparametric Tests for Comparing Means - A Personal Summary

Exact Nonparametric Tests for Comparing Means - A Personal Summary Exact Nonparametric Tests for Comparing Means - A Personal Summary Karl H. Schlag European University Institute 1 December 14, 2006 1 Economics Department, European University Institute. Via della Piazzuola

More information

MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS

MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS Systems of Equations and Matrices Representation of a linear system The general system of m equations in n unknowns can be written a x + a 2 x 2 + + a n x n b a

More information

Section 1.3 P 1 = 1 2. = 1 4 2 8. P n = 1 P 3 = Continuing in this fashion, it should seem reasonable that, for any n = 1, 2, 3,..., = 1 2 4.

Section 1.3 P 1 = 1 2. = 1 4 2 8. P n = 1 P 3 = Continuing in this fashion, it should seem reasonable that, for any n = 1, 2, 3,..., = 1 2 4. Difference Equations to Differential Equations Section. The Sum of a Sequence This section considers the problem of adding together the terms of a sequence. Of course, this is a problem only if more than

More information

1 Review of Newton Polynomials

1 Review of Newton Polynomials cs: introduction to numerical analysis 0/0/0 Lecture 8: Polynomial Interpolation: Using Newton Polynomials and Error Analysis Instructor: Professor Amos Ron Scribes: Giordano Fusco, Mark Cowlishaw, Nathanael

More information

9.2 Summation Notation

9.2 Summation Notation 9. Summation Notation 66 9. Summation Notation In the previous section, we introduced sequences and now we shall present notation and theorems concerning the sum of terms of a sequence. We begin with a

More information

sin(x) < x sin(x) x < tan(x) sin(x) x cos(x) 1 < sin(x) sin(x) 1 < 1 cos(x) 1 cos(x) = 1 cos2 (x) 1 + cos(x) = sin2 (x) 1 < x 2

sin(x) < x sin(x) x < tan(x) sin(x) x cos(x) 1 < sin(x) sin(x) 1 < 1 cos(x) 1 cos(x) = 1 cos2 (x) 1 + cos(x) = sin2 (x) 1 < x 2 . Problem Show that using an ɛ δ proof. sin() lim = 0 Solution: One can see that the following inequalities are true for values close to zero, both positive and negative. This in turn implies that On the

More information

LIMITS AND CONTINUITY

LIMITS AND CONTINUITY LIMITS AND CONTINUITY 1 The concept of it Eample 11 Let f() = 2 4 Eamine the behavior of f() as approaches 2 2 Solution Let us compute some values of f() for close to 2, as in the tables below We see from

More information

Constrained optimization.

Constrained optimization. ams/econ 11b supplementary notes ucsc Constrained optimization. c 2010, Yonatan Katznelson 1. Constraints In many of the optimization problems that arise in economics, there are restrictions on the values

More information

Examples of Tasks from CCSS Edition Course 3, Unit 5

Examples of Tasks from CCSS Edition Course 3, Unit 5 Examples of Tasks from CCSS Edition Course 3, Unit 5 Getting Started The tasks below are selected with the intent of presenting key ideas and skills. Not every answer is complete, so that teachers can

More information

How To Solve A Minimum Set Covering Problem (Mcp)

How To Solve A Minimum Set Covering Problem (Mcp) Measuring Rationality with the Minimum Cost of Revealed Preference Violations Mark Dean and Daniel Martin Online Appendices - Not for Publication 1 1 Algorithm for Solving the MASP In this online appendix

More information

Partial Fractions. Combining fractions over a common denominator is a familiar operation from algebra:

Partial Fractions. Combining fractions over a common denominator is a familiar operation from algebra: Partial Fractions Combining fractions over a common denominator is a familiar operation from algebra: From the standpoint of integration, the left side of Equation 1 would be much easier to work with than

More information