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Prascius 1 Steven Prascius Mrs. Tallman AP Calculus 31 March 2014 Sequences and Series In calculus, sequences and series are two important topics that allow for the approximation of functions and much more. Although sequences and series may seem to be the same thing, they are quite different from one another. A sequence is an infinite ordered list of numbers whereas a series is the summation of the numbers in a sequence. In other words, a sequence is list of numbers and a series is the sum of that list of numbers. So if given a finite list of the numbers one through five the sequence and series would be: Sequence: 1, 2, 3, 4, 5 While the series would be Series: 1+2+3+4+5 As seen in the example above, sequences and series both use the same terms but differ in that a sequence merely list the terms in a list and a series takes the sum of the list of terms. Both sequences and series have terms that follow the pattern t1, t2, t3β¦.tn ,β¦where the t1 is the first term, t2 is the second and so on with tn being the nth term in the list, with the sequence generally written as an. Since series are sums of sequences, they are written as βππ=1 (an) where β means summation and n=1 and n are the first and last terms of the sequence an. One thing sequences and series have in common is how they either converge or diverge. When a sequence converges it means that as the terms in the sequence approach infinity the Prascius 2 sequence will approach a single number, or limit. This is written as lim ππ = πΏ where an is the πββ sequence and L is the limit, or number, that the sequence approaches as it goes toward infinity. An example of a converging sequence is: 15 7 3 1 Converging sequence: 2, 116, 18, 14, 12β¦β¦β¦ As you can see the sequence is said to converge because the terms all approach 1 as they move toward infinity. On the other hand, if a sequence does not converge it is said to diverge. When a sequence diverges it means that it does not approach a single value as it goes to either positive or negative infinity. This is written as lim ππ = β. An example of a diverging sequence is: πββ Diverging sequence: 2, 4, 6, 8, 10, 12, 14β¦β¦ As you can see the sequence is said to diverge because the terms do not approach a single value as they move toward infinity, they just keep on going. A series converges if and only if its sequence of partial sums converges. This means that if the terms in a sequence converge for a certain range then the series of that sequence converge as well. If not then the series is said to diverge. Usually a series diverges or converges depending on whether the sequence converges or diverges, but there are situations when a sequence converges but the series diverges. One such example is the harmonic series 1/n. When this series is written out as the sequence 1, 1/2, 1/3, 1/4... it is clear that it converges because the terms approach zero. The series, however, diverges because the terms when added together approach infinity. This can be seen in figure 1. Prascius 3 Figure 1. Harmonic series Figure 1 shows how the series (in blue) diverges while the sequence (in red) converges. Relating to sequences and series are Taylor and Maclaurin series. Taylor and Maclaurin series allow any function f(x) to be written as an infinite sum of terms around a single point, x. Taylor and Maclaurin series are calculated in the same way, with the derivative of the function f(x) being taken several times and then having an x-value substituted into those derivative to get a single f(x) value. This f(x) value is then substituted into Taylor series expansion form which is: Where f(a), fβ(a), fββ(a), and f(3)(a) are the original function and its derivatives at the point a. This point a is equal to a point x on the function. In the case of a Maclaurin series, this a value is always equal to zero whereas in a Taylor series this a value can be any x-value. In short, Taylor Prascius 4 and Maclaurin series are almost the same thing with the only difference being that a Maclaurin series has to have a = 0. An example of a Taylor series can be seen when considering the function sin(x) about x=Ο/3. In order to calculate the coefficients of the Taylor series, the derivatives of sin(x) must be taken at x=Ο/3 which comes out to be: f(x) = sin(x) f(Ο/3) = β3/2 fβ(x) = cos(x) fβ(Ο/3) = 1/2 fββ(x) = -sin(x) fββ(Ο/3) = ββ3/2 f(3)(x) = -cos(x) f(3)(Ο/3) = -1/2 Once these derivatives are taken about x=Ο/3 they are plugged in as coefficients of the Taylor series which comes out to be: Sin(x) = β3/2 + 1/2(x-Ο/3) + ββ3/2 β1/2 2! 3! (x- Ο/3)2 + (x- Ο/3)3+β¦β¦ Finding the Maclaurin series of the same function at x=0 would come out to be: f(x) = sin(x) f(0) = 0 fβ(x) = cos(x) fβ0) = 1 fββ(x) = -sin(x) fββ(0) = 0 f(3)(x) = -cos(x) f(3)(0) = -1 Sin(x) = (x) + β1 3! (x) 3+β¦β¦ Prascius 5 Another thing series can do is approximate the values of functions. A series can approximate a value of a function by taking a partial sum at the x-value of that point. A partial sum is simply the sum of a finite number of terms in a series. For example we could use the 5th partial sum (5 terms) of the power series for ex to approximate e0.1. Since ex is one of the eight basic power series, it is known that its expansion is: 1 n ex = 1 + x + ½!*x2 + 1/3!*x3 + ¼!*x4 + β¦β¦..=ββ π=0 π! β π₯ In order to approximate e0.1 we would simply plug 0.1 into the above expansion for x which will give us an approximate answer for e0.1. When we do this it comes out to: 1 e0.1 = 1 + 0.1 + ½!*0.1 2 + 1/3!* 0.1 3 + ¼!*0.1 4 + β¦β¦..=β4π=0 π! β 0.1 n = 1.105170833 This approximation gives a value that is very close to the true value of e0.1 which is 1.105170918. The difference between the actual value and the approximate value is called the error. In this situation the error is equal to 0.000000085. Since the error is so small it shows that partial sums are an effective way of estimating the value of functions at certain points. This error in the above problem can be lessened by increasing the number of terms, n, used in the partial sum. The error calculated in the above example is known as the actual error and it is one of three ways to calculate error and it again simply involves subtracting the approximate value from the actual value. Another way to calculate error is by the alternating series method. The alternating series method states that the actual error will be no more than the absolute value of tn+1. The alternating series method only applies to functions which pass the alternating series test, which means that they converge. In order for a function to pass the alternating series test it must have terms that alternate signs, have tn+1 < tn, and have the limit as n approaches infinity equal to zero. Prascius 6 n One such series that passes the alternating series method applies to is ββ π=2(β1) * 1/ln(n). This series passes the alternating series test with each terms alternating signs, the limit as n approaches infinity equaling zero, and having the tn+1 term less than tn. The final way to calculate the error is the Lagrange method. The Lagrange method works by finding the remaining terms of a series, or tail, to estimate the accuracy of the estimated answer. This method states that the actual error must be less than or equal to the value of π |π₯ (π+1)! β π|n+1, with M being the maximum value of the functions derivative, n being the number of terms, and x being the value that the estimate is being taken around. All three of these methods accurately give the error between the estimated value of a function from a partial sum and the actual value. Sequences and series are two important topics in calculus. They allow for the expansion of functions into individual terms and even allow values of functions to be approximated accurately. Prascius 7 5. Solve the following questions: The function f is defined by the power series n f(x) = 1 + (x+1) + (x+1)2 +β¦+ (x+1)n +β¦.= ββ π=0(π₯ + 1) for all real numbers x for which the series converges. a) Find the interval of convergence of the power series for f. justify your answer. ο· ο· (π₯+1)π+1 lim (| πββ (π₯+1)π |) = |π₯ + 1|, so -1 < x + 1< 1, therefore -2 < x < 0 n When x = -2 you get ββ π=0(β1) which diverges by the nth term test because the limit as n approaches infinity does not equal 0. ο· n When x = 0 you get ββ π=0(1) which diverges by the nth term test as well because the limit as n approaches infinity does not equal zero. ο· The interval of convergence is -2 < x < 0 b) The power series above is the Taylor series for f about x = -1. Find the sum of the series for f ο· 1 1 n F(x) = ββ π=0(π₯ + 1) = 1β(π₯+1) = βπ₯ in the interval -2 < x < 0 π₯ c) Let g be the function defined by g(x) = β«β1 π(π‘)ππ‘. Find the value of g(-0.5), if it exists, or explain why g(-0.5) cannot be determined ο· β0.5 1 g(-0.5) = = β«β1 βπ₯ β0.5 ππ₯ = -ln|π₯| | = 0.6931 β1 d) Let h be the function defined by h(x) = f(x2-1). Find the first three non-zero terms and the general term of the Taylor series for h about x=0. Find the value of h(0.5). ο· h(x) = f(x2-1) = 1+ x2 + x4 +β¦β¦.x2n +β¦β¦ ο· n h(0.5) = f(-3/4) = ββ π=0(β3/4 + 1) = 4/3 Prascius 8 6. Which of the following series diverge? Be sure to address which test you have chosen and WHY you chose it. π1.5 +1 a) ββ π=0( 5π2 +7 ) π1.5 +1 1 β 2 ββ π=1( 5π2 +7 ) < βπ=0(π2 ) , this series converges because it is bound by the series 1/n which converges itself by the p-series test. I chose this test because it was easier than any other test that could be done. n b) ββ π=2(β1) * 1 ln(π) This series converges by the alternating series test. The series alternates, has a limit that 1 1 approaches zero as n approaches infinity, and has ln(π+1) < ln(π). Because this series fulfills all of these requirements it converges by the alternating series test. I chose this test because it was obvious that the alternating series test would work. 4 n n c) ββ π=0(β1) *( 3) 4 π/π 4 n n ββ π=0(β1) *( 3) = lim ( 3) πββ = 4/3 which is greater than 1 This series diverges by the root test. I chose the root test because the series had a root in it and I thought that it would be easiest to do the root test. 7. Find the interval of convergence. Be sure to check the endpoints. ο· ο· lim |( πββ 2π₯ π+1 π+2 2π₯π )/(π+1)| = |2π₯| so -1/2 < x < 1/2 n When x =-1/2 you get ββ π=0(β1) /n+1 which converges by the alternating series test. The alternating series test applies because the series alternates signs, 1/n+2 < 1/n+1, and Prascius 9 the limit as n approaches infinity is zero. I chose to the alternating series test because it was apparent that the series fit that test the best. ο· n When x = ½ you get ββ π=0(1) /n+1 which diverges by the limit comparison test when compared to 1/n. This written out comes out to be lim (1n/n+1)/(1n/n) = lim (n/n+1) = πββ πββ 1. Since the limit is equal to a positive real number both series behave the same so since n 1/n diverges by the p-series test so does ββ π=0(1) /n+1. ο· The interval of convergence is -1/2 <= x < 1/2 Prascius 10 Works Cited Swift. "MAT 137, Calculus II." MAT 137, Professor Swift. N.p., n.d. Web. 30 Mar. 2014. "Taylor Series." Wikipedia. Wikimedia Foundation, 30 Mar. 2014. Web. 30 Mar. 2014.