APPROXIMATE INTEGRATION
|
|
- Tracy Wilkinson
- 5 years ago
- Views:
Transcription
1 APPROXIMATE INTEGRATION. Introduction We hve seen tht there re functions whose nti-derivtives cnnot be expressed in closed form. For these resons ny definite integrl involving these integrnds cnnot be determined in n exct mnner. Alterntively, function my only be determined by scientific experiment in the form of tbles of dt. In this sitution there my be no formul for the function. In these cses we cn find pproximte vlues of definite integrls. We hve lredy seen bsic pproch to this, nmely Riemnn sums. Any Riemnn sum could be used s n pproximtion to the ctul integrl. Tht is if we divide [, b] into n subintervls of equl length x = b n then we hve f(x)dx f(x i ) x i= where x i is ny point in the i th subintervl [x i, x i ]. If we choose x i to be the left endpoint of the intervl, x i = x i then () f(x)dx L n = f(x i ) x. A If f(x), the integrl represents n re nd () will be n pproximtion of this re by n rectngles. If insted we choose the right endpoint s x i, so tht x i = x i, then () f(x)dx R n = f(x i ) x A The pproximtions L n nd R n defined by equtions () nd () re clled (unsurprisingly) the left endpoint pproximtion nd right endpoint pproximtion respectively. i= i=. Other Approximtions These re not the only pproximtions possible. If one chose x i to be the midpoint x i of the subintervl [x i, x i ] we produce the midpoint pproximtion M n which will perform better thn L n or R n. Proposition.. MidPoint Rule A f(x)dx M n = where x = b n nd x i = (x i + x i ) f( x i ) x i=
2 APPROXIMATE INTEGRATION Another pproximtion tht is more ccurte thn L n or R n is the Trpezoidl Rule which cn be found by verging equtions () nd (): [ f(x)dx n f(x i ) x + i= ] f(x i ) x i= = x [ n ] f(x i ) + f(x i ) = x [(f(x ) + f(x )) + (f(x ) + f(x )) (f(x n ) + f(x n ))] = x [f(x ) + f(x ) + f(x ) f(x n ) + f(x n )] This pproch cn be summrized s the following formul Proposition.. Trpezoidl Rule [ ] b f(x)dx T n = x n f(x ) + f(x i ) + f(x n ) where x = b x nd x i = + i x For f(x) the nme of the Trpezoidl rule becomes pprent if one drws the sums for prticulr function; we re no longer dding rectngles, but trpezoids over ech subintervl with the re of the i th trpezoid: ( ) f(xi + f(x i ) x = x [f(x i ) + f(x i )]. Adding up the re of ech trpezoids we recover the bove formul. i= Exmple.3. For n = 5, evlute the integrl () the Trpezoidl Rule () the Midpoint rule xdx using i= Proof. () Plugging in n = 5, = nd b = x = b x Trpezoidl rule produces = 5 =. nd the x dx T 5 =. (f() + f(.) + f(.4) + f(.6) + f(.8) + f()) ( = ) () Averging the six points, we hve x dx M 5 = x[f(.) + f(.3) + f(.5) + f(.7) + f(.9)] = ( )
3 APPROXIMATE INTEGRATION 3 3. Error Bounds This exmple ws delibertely chosen so tht its exct vlue could be computed, nd comprison of ccurcy could be drwn between the trpezoidl nd midpoint rules. The Fundmentl Theorem of clculus implies x dx = ln x] = ln = The error in using n pproximtion is defined to be the mount tht must be dded to mke the pproximtion equl the exct vlue. From exmple, we my compute the errors for n=5 from the trpezoidl nd midpoint rule to be More generlly, these re E T = E T.488, E M.39. f(x)dx T n, E M = f(x)dx M n. To compre the ccurcy of ech of L n, R n, M n nd T n consider the following tbles for n = 5,, nd n L n R n T n M n n E L E R E T E M From this tble, one cn mke the following observtions For ll of the methods, if we increse the vlue of n the pproximtion becomes more ccurte. Bewre lrge vlues of n due to the round-off error rising from the lrge number of rithmetic opertions. The error in the left nd right endpoint pproximtion hve opposite sign nd their error decresed by fctor of when n is doubled. The Trpezoidl nd Midpoint rule re better pproximtions thn the endpoint pproximtions. The trpezoidl nd midpoint rules hve error with opposite sign nd they decrese by rougly fctor of 4 by doubling n The mgnitude of the error for the Midpoint rule is roughly hlf the size of the error for the Trpezoidl rule. This lst fct cn be proven with elementry geometry - see Figure 5 in chpter 7.5 of the textbook. Any textbook in numericl nlysis will support these observtions. For exmple the fourth observtion rises from the fct tht n is involved in the sum, so tht (n) = 4n. As f (x) mesures how much the grph curves, the estimtes will depend on the size of the second derivtive of f(x)
4 4 APPROXIMATE INTEGRATION Proposition 3.. Error Bounds If f (x) K for x [, b], then the error bounds for the Trpezoidl nd Midpoint rule re respectively bounded by E T K(b )3 K(b )3 n, nd E M 4n Returning to exmple, we cn determine the error estimte for the Trpezoidl rule. With f(x) = x, f (x) = x nd f (x) = x, then since /x for x [, ] 3 f (x) = 3 =. x 3 Choosing K =, with =, b = nd n = 5 the error estimte from Proposition 3. will be ( )3 E T 5 = The ctul error for this exmple ws.488 <.6667, this shows it cn hppen tht the ctul error is substntilly less thn the upper bound for the error given by Proposition 3.. Exmple 3.. How lrge should n be chosen in order to gurntee the Trpezoidl nd Midpoint rule pproximte xdx to within.? Proof. Previously we sw tht f (x) for x [, ], thus tking K =, =, b = nd leving n rbitrry we hve Solving the inequlity for n, () 3 n. n > (.) n > (.6) 4.8 Choosing the lrger integer, n = 4 will ensure the desired ccurcy. Repeting this process for the Midpoint rule error bound 9 () 3 4n <. n > (.) Exmple 3.3. () Use the Midpoint Rule with n = to pproximte the integrl ex dx. () Give n upper bound for the error involved in this pproximtion. Proof. () Since =, b = nd n = we hve x =. nd the Midpoint rule yields e x dx x[f(.5) + f(.) f(.85) + f(.95)] =.[e.5 + e.5 + e.65 + e.5 + e.5 + e.35 +e.45 + e e.75 + e.95 ].46393
5 APPROXIMATE INTEGRATION 5 () As f(x) = e x, then f (x) = xe x nd f (x) = ( + 4x)e x As x for ll x [, ] this implies f (x) = ( + 4x )e x 6e Choosing K = 6e, =, b =, nd n = in the error estimte of Proposition 3. the upper bound for the error is 6e() 3 4() = e Simpson s Rule As n lterntive to using stright line segments to pproximte curve, we could use prbols insted. We divide the intervl [, b] into n subintervls of equl length h = x = b n, however now we require tht n is even. For ech consecutive pir of intervls we pproximte the curve y = f(x) by prbol. If y i = f(x i ) then P i (x i, y i ) is the point on the curve lying bove x i. Typiclly prbol psses through three consecutive points P i, P i+, nd P i+. For moment, let us suppose tht x = h, x = nd x = h, to mke our clcultion simpler. It is known tht the eqution of the prbol through P, P, nd P is of the form y = Ax + Bx + C nd the re under the prbol from x = h to x = h is h h (Ax + Bx + C)dx = h (Ax + C)dx ] h = [A x3 3 + Cx ) = (A h3 3 + Ch = h 3 (Ah + 6C). As the point psses through P ( h, y ), P (, y ), nd P (h, y ) implying thus y = A( h) + B( h) + C = Ah Bh + C y = C y = Ah + Bh + C y + 4y + y = Ah + 6C. Therefore we cn rewrite the re under the prbol s h 3 (y + 4y + y ) If we shift the prbol horizontlly we do not chnge the re under it. The re under the prbol through P, P 3, nd P 4 from x = x to x = x 4 is lso h 3 (y + 4y 3 + y 4 )
6 6 APPROXIMATE INTEGRATION Computing the res under ll of the prbols in this mnner nd dding the res together, A f(x)dx h 3 (y + 4y + y ) + h 3 (y + 4y 3 + y 4 ) h 3 (y n + 4y n + y n ) = h 3 (y + 4y + y + 4y 3 + y y n + 4y n + y n While we only considered the cse where f(x), this pproch will work for ny continuous function f. This pproximtion is clled Simpson s Rule nd it is nmed fter the English mthemticin Thoms Simpson (7-76). It is importnt to remember the pttern of the coefficients, 4,, 4,, 4,,..., 4,, 4, ]. Proposition 4.. Simpson s Rule f(x)dx S n = x 3 [f(x ) + 4f(x ) + f(x ) + 4f(x 3 ) +... where n is even nd x = b x. +f(x n ) + 4f(x n ) + f(x n )] Exmple 4.. Use Simpson s Rule with n = to pproximte x dx Proof. Setting f(x) = /x, n =, = nd b = then x =. nd Simpson s rule yields x dx = [f() + 4f(.) + f(.) + 4f(.3) +...f(.8) + 4f(.9) + f()] x 3 =. ( ).6935 Compring with our previous exmple, it is cler tht Simpson s Rule gives significntly better pproximtion S.6935) to the true vlue of the integrl ln ). In fct, one cn prove tht the pproximtions in Simpson s Rule re weighted verges of those in the Trpezoidl nd Midpoint rules: S n = 3 T n + 3 M n It hs been mentioned tht often one must evlute n integrl even if one hs no explicit formul for y s function of x. Tht is, the function my be given grphiclly or s tble of vlues of collected dt. If the vlues do not chnge rpidly, the Trpezoidl rule or Simpson s rule cn be used to determine n pproximte vlue for ydx. Exmple 4.3. The following figure shows dt trffic on the link from the United Sttes to SWITCH the Swiss Acdemic nd Reserch Network on Februry, 998. Use Simpson s Rule to estimte the totl mount of dt trnsmitted on the link from midnight to noon on tht dy. Proof. As D(t) is mesured in megbits per second, we hve to convert the units for t from hours to seconds. Defining A(t) s the mount of dt trnsmitted by
7 APPROXIMATE INTEGRATION 7 Figure. Grph of D(t) dt throughput, mesured in Mb/s time t, where t is mesured in seconds, then A (t) = D(t). From the Net Chnge Theorem, the totl mount of dt trnsmitted by noon (t = x6 = 43, ) is A(43, ) = 43, D(t)dt. Estimting the vlues of D(t) t hourly intervls from the grph: t(hours) t(seconds) D(t) 3. 3, 6.7 7,.9 3, , ,. 6, ,.3 8 8, , , 7. 39, , 7.9 Using Simpson s rule with n = nd t = 36 to estimte the integrl 43 D(t)dt t [D() + 4D(36) + D(7) D(39, 6) + D(43, )] 3 36 [3.4(.7) + (.9) + 4(.7) + (.3) + 4(.) + (.) + 4(.3) 3 +(.8) + 4(5.7) + (7.) + 4(7.7) + 7.9] = 43, 88
8 8 APPROXIMATE INTEGRATION Thus the totl mount of dt trnsmitted from midnight to noon is 44, megbits or 44 gigbits. We cn compre the Simpson s rule nd the Midpoint rule, in the first tble, for the integrl xdx whise ctul vlue is In the second tble we cn compute the error for ech pproximtion. Notice tht E s decreses by fctor of bout 6 when n is doubled. This fct is consistent with the following error bound for Simpson s rule n M n S n n M n S n Proposition 4.4. Error Bound for Simpson s Rule Suppose tht f (4) (x) K for x b. If E s is the error involved in using Simpson s Rule then E s K(b )5 8n 4 Exmple 4.5. How lrge should we tke n in order to gurntee tht the Simpson s Rule pproximtion for xdx is ccurte to within.? Proof. Since f(x) = /x then f(x) = 4/x 5 ; requiring x, /x nd so f (4) (x) = 4 4 x 5 Therefore we cn tke K = 4. Requiring tht the error is less thn. we choose n so tht This yields which gives n > 4() 5 8n 4 <. n 4 > 4 8(.) Since n must be even, n = 8 will give us the ccurcy we require. This is pretty good compred to n = 9 for the midpoint rule nd n = 4 for the Trpezoidl rule. Exmple 4.6. () Use Simpson s Rule with n = to pproximte the integrl ex dx. () Estimte the error involved in this pproximtion.
9 Proof. APPROXIMATE INTEGRATION 9 () If n =, = nd b =, Simpson s rule gives e x dx x [f() + 4f(.) + f(.) f(.8) + 4f(.9) + f()] 3 =. 3 [e + 4e. + e.4 + 4e.9 + e.6 + 4e.5 + e.36 +4e.49 + e e.8 + e ].4668 () The fourth derivtive of f(x) = e x is nd since x we hve f (4) (x) = ( + 48x + 6x 4 )e x ( )e = 76e. Setting K = 76e, with =, b = nd n = the error is 76e() 5 8() 4.5 From this we know the correct nswer to three deciml plces is e x dx.463
Midpoint Approximation
Midpoint Approximtion Sometimes, we need to pproximte n integrl of the form R b f (x)dx nd we cnnot find n ntiderivtive in order to evlute the integrl. Also we my need to evlute R b f (x)dx where we do
More informationMath& 152 Section Integration by Parts
Mth& 5 Section 7. - Integrtion by Prts Integrtion by prts is rule tht trnsforms the integrl of the product of two functions into other (idelly simpler) integrls. Recll from Clculus I tht given two differentible
More information6.5 Numerical Approximations of Definite Integrals
Arknss Tech University MATH 94: Clculus II Dr. Mrcel B. Finn 6.5 Numericl Approximtions of Definite Integrls Sometimes the integrl of function cnnot be expressed with elementry functions, i.e., polynomil,
More informationMath 131. Numerical Integration Larson Section 4.6
Mth. Numericl Integrtion Lrson Section. This section looks t couple of methods for pproimting definite integrls numericlly. The gol is to get good pproimtion of the definite integrl in problems where n
More informationZ b. f(x)dx. Yet in the above two cases we know what f(x) is. Sometimes, engineers want to calculate an area by computing I, but...
Chpter 7 Numericl Methods 7. Introduction In mny cses the integrl f(x)dx cn be found by finding function F (x) such tht F 0 (x) =f(x), nd using f(x)dx = F (b) F () which is known s the nlyticl (exct) solution.
More informationSection 6.1 Definite Integral
Section 6.1 Definite Integrl Suppose we wnt to find the re of region tht is not so nicely shped. For exmple, consider the function shown elow. The re elow the curve nd ove the x xis cnnot e determined
More informationSuppose we want to find the area under the parabola and above the x axis, between the lines x = 2 and x = -2.
Mth 43 Section 6. Section 6.: Definite Integrl Suppose we wnt to find the re of region tht is not so nicely shped. For exmple, consider the function shown elow. The re elow the curve nd ove the x xis cnnot
More informationProperties of Integrals, Indefinite Integrals. Goals: Definition of the Definite Integral Integral Calculations using Antiderivatives
Block #6: Properties of Integrls, Indefinite Integrls Gols: Definition of the Definite Integrl Integrl Clcultions using Antiderivtives Properties of Integrls The Indefinite Integrl 1 Riemnn Sums - 1 Riemnn
More informationMath 1B, lecture 4: Error bounds for numerical methods
Mth B, lecture 4: Error bounds for numericl methods Nthn Pflueger 4 September 0 Introduction The five numericl methods descried in the previous lecture ll operte by the sme principle: they pproximte the
More informationLecture 14: Quadrature
Lecture 14: Qudrture This lecture is concerned with the evlution of integrls fx)dx 1) over finite intervl [, b] The integrnd fx) is ssumed to be rel-vlues nd smooth The pproximtion of n integrl by numericl
More informationThe Regulated and Riemann Integrals
Chpter 1 The Regulted nd Riemnn Integrls 1.1 Introduction We will consider severl different pproches to defining the definite integrl f(x) dx of function f(x). These definitions will ll ssign the sme vlue
More informationGoals: Determine how to calculate the area described by a function. Define the definite integral. Explore the relationship between the definite
Unit #8 : The Integrl Gols: Determine how to clculte the re described by function. Define the definite integrl. Eplore the reltionship between the definite integrl nd re. Eplore wys to estimte the definite
More informationNUMERICAL INTEGRATION. The inverse process to differentiation in calculus is integration. Mathematically, integration is represented by.
NUMERICAL INTEGRATION 1 Introduction The inverse process to differentition in clculus is integrtion. Mthemticlly, integrtion is represented by f(x) dx which stnds for the integrl of the function f(x) with
More informationThe Trapezoidal Rule
_.qd // : PM Pge 9 SECTION. Numericl Integrtion 9 f Section. The re of the region cn e pproimted using four trpezoids. Figure. = f( ) f( ) n The re of the first trpezoid is f f n. Figure. = Numericl Integrtion
More informationSections 5.2: The Definite Integral
Sections 5.2: The Definite Integrl In this section we shll formlize the ides from the lst section to functions in generl. We strt with forml definition.. The Definite Integrl Definition.. Suppose f(x)
More informationDefinite integral. Mathematics FRDIS MENDELU
Definite integrl Mthemtics FRDIS MENDELU Simon Fišnrová Brno 1 Motivtion - re under curve Suppose, for simplicity, tht y = f(x) is nonnegtive nd continuous function defined on [, b]. Wht is the re of the
More informationINTRODUCTION TO INTEGRATION
INTRODUCTION TO INTEGRATION 5.1 Ares nd Distnces Assume f(x) 0 on the intervl [, b]. Let A be the re under the grph of f(x). b We will obtin n pproximtion of A in the following three steps. STEP 1: Divide
More informationDefinite integral. Mathematics FRDIS MENDELU. Simona Fišnarová (Mendel University) Definite integral MENDELU 1 / 30
Definite integrl Mthemtics FRDIS MENDELU Simon Fišnrová (Mendel University) Definite integrl MENDELU / Motivtion - re under curve Suppose, for simplicity, tht y = f(x) is nonnegtive nd continuous function
More informationA REVIEW OF CALCULUS CONCEPTS FOR JDEP 384H. Thomas Shores Department of Mathematics University of Nebraska Spring 2007
A REVIEW OF CALCULUS CONCEPTS FOR JDEP 384H Thoms Shores Deprtment of Mthemtics University of Nebrsk Spring 2007 Contents Rtes of Chnge nd Derivtives 1 Dierentils 4 Are nd Integrls 5 Multivrite Clculus
More informationThe Fundamental Theorem of Calculus, Particle Motion, and Average Value
The Fundmentl Theorem of Clculus, Prticle Motion, nd Averge Vlue b Three Things to Alwys Keep In Mind: (1) v( dt p( b) p( ), where v( represents the velocity nd p( represents the position. b (2) v ( dt
More informationDistance And Velocity
Unit #8 - The Integrl Some problems nd solutions selected or dpted from Hughes-Hllett Clculus. Distnce And Velocity. The grph below shows the velocity, v, of n object (in meters/sec). Estimte the totl
More informationTangent Line and Tangent Plane Approximations of Definite Integral
Rose-Hulmn Undergrdute Mthemtics Journl Volume 16 Issue 2 Article 8 Tngent Line nd Tngent Plne Approximtions of Definite Integrl Meghn Peer Sginw Vlley Stte University Follow this nd dditionl works t:
More informationMath 8 Winter 2015 Applications of Integration
Mth 8 Winter 205 Applictions of Integrtion Here re few importnt pplictions of integrtion. The pplictions you my see on n exm in this course include only the Net Chnge Theorem (which is relly just the Fundmentl
More informationDefinite Integrals. The area under a curve can be approximated by adding up the areas of rectangles = 1 1 +
Definite Integrls --5 The re under curve cn e pproximted y dding up the res of rectngles. Exmple. Approximte the re under y = from x = to x = using equl suintervls nd + x evluting the function t the left-hnd
More informationNumerical Integration
Chpter 5 Numericl Integrtion Numericl integrtion is the study of how the numericl vlue of n integrl cn be found. Methods of function pproximtion discussed in Chpter??, i.e., function pproximtion vi the
More informationdifferent methods (left endpoint, right endpoint, midpoint, trapezoid, Simpson s).
Mth 1A with Professor Stnkov Worksheet, Discussion #41; Wednesdy, 12/6/217 GSI nme: Roy Zho Problems 1. Write the integrl 3 dx s limit of Riemnn sums. Write it using 2 intervls using the 1 x different
More information5.1 How do we Measure Distance Traveled given Velocity? Student Notes
. How do we Mesure Distnce Trveled given Velocity? Student Notes EX ) The tle contins velocities of moving cr in ft/sec for time t in seconds: time (sec) 3 velocity (ft/sec) 3 A) Lel the x-xis & y-xis
More informationBig idea in Calculus: approximation
Big ide in Clculus: pproximtion Derivtive: f (x) = df dx f f(x +h) f(x) =, x h rte of chnge is pproximtely the rtio of chnges in the function vlue nd in the vrible in very short time Liner pproximtion:
More informationAdvanced Calculus: MATH 410 Notes on Integrals and Integrability Professor David Levermore 17 October 2004
Advnced Clculus: MATH 410 Notes on Integrls nd Integrbility Professor Dvid Levermore 17 October 2004 1. Definite Integrls In this section we revisit the definite integrl tht you were introduced to when
More informationP 3 (x) = f(0) + f (0)x + f (0) 2. x 2 + f (0) . In the problem set, you are asked to show, in general, the n th order term is a n = f (n) (0)
1 Tylor polynomils In Section 3.5, we discussed how to pproximte function f(x) round point in terms of its first derivtive f (x) evluted t, tht is using the liner pproximtion f() + f ()(x ). We clled this
More informationNumerical Analysis: Trapezoidal and Simpson s Rule
nd Simpson s Mthemticl question we re interested in numericlly nswering How to we evlute I = f (x) dx? Clculus tells us tht if F(x) is the ntiderivtive of function f (x) on the intervl [, b], then I =
More informationChapter 6 Notes, Larson/Hostetler 3e
Contents 6. Antiderivtives nd the Rules of Integrtion.......................... 6. Are nd the Definite Integrl.................................. 6.. Are............................................ 6. Reimnn
More informationThe Riemann Integral
Deprtment of Mthemtics King Sud University 2017-2018 Tble of contents 1 Anti-derivtive Function nd Indefinite Integrls 2 3 4 5 Indefinite Integrls & Anti-derivtive Function Definition Let f : I R be function
More information1 The Riemann Integral
The Riemnn Integrl. An exmple leding to the notion of integrl (res) We know how to find (i.e. define) the re of rectngle (bse height), tringle ( (sum of res of tringles). But how do we find/define n re
More informationThe Fundamental Theorem of Calculus. The Total Change Theorem and the Area Under a Curve.
Clculus Li Vs The Fundmentl Theorem of Clculus. The Totl Chnge Theorem nd the Are Under Curve. Recll the following fct from Clculus course. If continuous function f(x) represents the rte of chnge of F
More informationChapter 2. Numerical Integration also called quadrature. 2.2 Trapezoidal Rule. 2.1 A basic principle Extending the Trapezoidal Rule DRAWINGS
S Cpter Numericl Integrtion lso clled qudrture Te gol of numericl integrtion is to pproximte numericlly. f(x)dx Tis is useful for difficult integrls like sin(x) ; sin(x ); x + x 4 Or worse still for multiple-dimensionl
More informationx = b a n x 2 e x dx. cdx = c(b a), where c is any constant. a b
CHAPTER 5. INTEGRALS 61 where nd x = b n x i = 1 (x i 1 + x i ) = midpoint of [x i 1, x i ]. Problem 168 (Exercise 1, pge 377). Use the Midpoint Rule with the n = 4 to pproximte 5 1 x e x dx. Some quick
More informationLecture 20: Numerical Integration III
cs4: introduction to numericl nlysis /8/0 Lecture 0: Numericl Integrtion III Instructor: Professor Amos Ron Scribes: Mrk Cowlishw, Yunpeng Li, Nthnel Fillmore For the lst few lectures we hve discussed
More informationUnit #9 : Definite Integral Properties; Fundamental Theorem of Calculus
Unit #9 : Definite Integrl Properties; Fundmentl Theorem of Clculus Gols: Identify properties of definite integrls Define odd nd even functions, nd reltionship to integrl vlues Introduce the Fundmentl
More informationReview of Calculus, cont d
Jim Lmbers MAT 460 Fll Semester 2009-10 Lecture 3 Notes These notes correspond to Section 1.1 in the text. Review of Clculus, cont d Riemnn Sums nd the Definite Integrl There re mny cses in which some
More informationThe Fundamental Theorem of Calculus
The Fundmentl Theorem of Clculus MATH 151 Clculus for Mngement J. Robert Buchnn Deprtment of Mthemtics Fll 2018 Objectives Define nd evlute definite integrls using the concept of re. Evlute definite integrls
More informationNUMERICAL INTEGRATION
NUMERICAL INTEGRATION How do we evlute I = f (x) dx By the fundmentl theorem of clculus, if F (x) is n ntiderivtive of f (x), then I = f (x) dx = F (x) b = F (b) F () However, in prctice most integrls
More informationChapter 7 Notes, Stewart 8e. 7.1 Integration by Parts Trigonometric Integrals Evaluating sin m x cos n (x) dx...
Contents 7.1 Integrtion by Prts................................... 2 7.2 Trigonometric Integrls.................................. 8 7.2.1 Evluting sin m x cos n (x)......................... 8 7.2.2 Evluting
More informationAP Calculus AB Unit 5 (Ch. 6): The Definite Integral: Day 12 Chapter 6 Review
AP Clculus AB Unit 5 (Ch. 6): The Definite Integrl: Dy Nme o Are Approximtions Riemnn Sums: LRAM, MRAM, RRAM Chpter 6 Review Trpezoidl Rule: T = h ( y + y + y +!+ y + y 0 n n) **Know how to find rectngle
More information1 Part II: Numerical Integration
Mth 4 Lb 1 Prt II: Numericl Integrtion This section includes severl techniques for getting pproimte numericl vlues for definite integrls without using ntiderivtives. Mthemticll, ect nswers re preferble
More informationMath 190 Chapter 5 Lecture Notes. Professor Miguel Ornelas
Mth 19 Chpter 5 Lecture Notes Professor Miguel Ornels 1 M. Ornels Mth 19 Lecture Notes Section 5.1 Section 5.1 Ares nd Distnce Definition The re A of the region S tht lies under the grph of the continuous
More informationReview of basic calculus
Review of bsic clculus This brief review reclls some of the most importnt concepts, definitions, nd theorems from bsic clculus. It is not intended to tech bsic clculus from scrtch. If ny of the items below
More informationNumerical Analysis. 10th ed. R L Burden, J D Faires, and A M Burden
Numericl Anlysis 10th ed R L Burden, J D Fires, nd A M Burden Bemer Presenttion Slides Prepred by Dr. Annette M. Burden Youngstown Stte University July 9, 2015 Chpter 4.1: Numericl Differentition 1 Three-Point
More informationa < a+ x < a+2 x < < a+n x = b, n A i n f(x i ) x. i=1 i=1
Mth 33 Volume Stewrt 5.2 Geometry of integrls. In this section, we will lern how to compute volumes using integrls defined by slice nlysis. First, we recll from Clculus I how to compute res. Given the
More informationImproper Integrals. Type I Improper Integrals How do we evaluate an integral such as
Improper Integrls Two different types of integrls cn qulify s improper. The first type of improper integrl (which we will refer to s Type I) involves evluting n integrl over n infinite region. In the grph
More informationIntegrals - Motivation
Integrls - Motivtion When we looked t function s rte of chnge If f(x) is liner, the nswer is esy slope If f(x) is non-liner, we hd to work hrd limits derivtive A relted question is the re under f(x) (but
More informationChapters 4 & 5 Integrals & Applications
Contents Chpters 4 & 5 Integrls & Applictions Motivtion to Chpters 4 & 5 2 Chpter 4 3 Ares nd Distnces 3. VIDEO - Ares Under Functions............................................ 3.2 VIDEO - Applictions
More informationRiemann is the Mann! (But Lebesgue may besgue to differ.)
Riemnn is the Mnn! (But Lebesgue my besgue to differ.) Leo Livshits My 2, 2008 1 For finite intervls in R We hve seen in clss tht every continuous function f : [, b] R hs the property tht for every ɛ >
More information1 The fundamental theorems of calculus.
The fundmentl theorems of clculus. The fundmentl theorems of clculus. Evluting definite integrls. The indefinite integrl- new nme for nti-derivtive. Differentiting integrls. Tody we provide the connection
More information7.2 The Definite Integral
7.2 The Definite Integrl the definite integrl In the previous section, it ws found tht if function f is continuous nd nonnegtive, then the re under the grph of f on [, b] is given by F (b) F (), where
More informationLab 11 Approximate Integration
Nme Student ID # Instructor L Period Dte Due L 11 Approximte Integrtion Ojectives 1. To ecome fmilir with the right endpoint rule, the trpezoidl rule, nd Simpson's rule. 2. To compre nd contrst the properties
More informationMATH , Calculus 2, Fall 2018
MATH 36-2, 36-3 Clculus 2, Fll 28 The FUNdmentl Theorem of Clculus Sections 5.4 nd 5.5 This worksheet focuses on the most importnt theorem in clculus. In fct, the Fundmentl Theorem of Clculus (FTC is rgubly
More informationSection 4.8. D v(t j 1 ) t. (4.8.1) j=1
Difference Equtions to Differentil Equtions Section.8 Distnce, Position, nd the Length of Curves Although we motivted the definition of the definite integrl with the notion of re, there re mny pplictions
More informationLecture 12: Numerical Quadrature
Lecture 12: Numericl Qudrture J.K. Ryn@tudelft.nl WI3097TU Delft Institute of Applied Mthemtics Delft University of Technology 5 December 2012 () Numericl Qudrture 5 December 2012 1 / 46 Outline 1 Review
More informationx = b a N. (13-1) The set of points used to subdivide the range [a, b] (see Fig. 13.1) is
Jnury 28, 2002 13. The Integrl The concept of integrtion, nd the motivtion for developing this concept, were described in the previous chpter. Now we must define the integrl, crefully nd completely. According
More informationf(x) dx, If one of these two conditions is not met, we call the integral improper. Our usual definition for the value for the definite integral
Improper Integrls Every time tht we hve evluted definite integrl such s f(x) dx, we hve mde two implicit ssumptions bout the integrl:. The intervl [, b] is finite, nd. f(x) is continuous on [, b]. If one
More information1 The fundamental theorems of calculus.
The fundmentl theorems of clculus. The fundmentl theorems of clculus. Evluting definite integrls. The indefinite integrl- new nme for nti-derivtive. Differentiting integrls. Theorem Suppose f is continuous
More informationIndefinite Integral. Chapter Integration - reverse of differentiation
Chpter Indefinite Integrl Most of the mthemticl opertions hve inverse opertions. The inverse opertion of differentition is clled integrtion. For exmple, describing process t the given moment knowing the
More informationDOING PHYSICS WITH MATLAB MATHEMATICAL ROUTINES
DOIG PHYSICS WITH MATLAB MATHEMATICAL ROUTIES COMPUTATIO OF OE-DIMESIOAL ITEGRALS In Cooper School of Physics, University of Sydney in.cooper@sydney.edu.u DOWLOAD DIRECTORY FOR MATLAB SCRIPTS mth_integrtion_1d.m
More information63. Representation of functions as power series Consider a power series. ( 1) n x 2n for all 1 < x < 1
3 9. SEQUENCES AND SERIES 63. Representtion of functions s power series Consider power series x 2 + x 4 x 6 + x 8 + = ( ) n x 2n It is geometric series with q = x 2 nd therefore it converges for ll q =
More informationWe divide the interval [a, b] into subintervals of equal length x = b a n
Arc Length Given curve C defined by function f(x), we wnt to find the length of this curve between nd b. We do this by using process similr to wht we did in defining the Riemnn Sum of definite integrl:
More informationSection 6: Area, Volume, and Average Value
Chpter The Integrl Applied Clculus Section 6: Are, Volume, nd Averge Vlue Are We hve lredy used integrls to find the re etween the grph of function nd the horizontl xis. Integrls cn lso e used to find
More informationTopics Covered AP Calculus AB
Topics Covered AP Clculus AB ) Elementry Functions ) Properties of Functions i) A function f is defined s set of ll ordered pirs (, y), such tht for ech element, there corresponds ectly one element y.
More informationExam 2, Mathematics 4701, Section ETY6 6:05 pm 7:40 pm, March 31, 2016, IH-1105 Instructor: Attila Máté 1
Exm, Mthemtics 471, Section ETY6 6:5 pm 7:4 pm, Mrch 1, 16, IH-115 Instructor: Attil Máté 1 17 copies 1. ) Stte the usul sufficient condition for the fixed-point itertion to converge when solving the eqution
More information4.6 Numerical Integration
.6 Numericl Integrtion 5.6 Numericl Integrtion Approimte definite integrl using the Trpezoidl Rule. Approimte definite integrl using Simpson s Rule. Anlze the pproimte errors in the Trpezoidl Rule nd Simpson
More information!0 f(x)dx + lim!0 f(x)dx. The latter is sometimes also referred to as improper integrals of the. k=1 k p converges for p>1 and diverges otherwise.
Chpter 7 Improper integrls 7. Introduction The gol of this chpter is to meningfully extend our theory of integrls to improper integrls. There re two types of so-clled improper integrls: the first involves
More information5.7 Improper Integrals
458 pplictions of definite integrls 5.7 Improper Integrls In Section 5.4, we computed the work required to lift pylod of mss m from the surfce of moon of mss nd rdius R to height H bove the surfce of the
More informationMath 360: A primitive integral and elementary functions
Mth 360: A primitive integrl nd elementry functions D. DeTurck University of Pennsylvni October 16, 2017 D. DeTurck Mth 360 001 2017C: Integrl/functions 1 / 32 Setup for the integrl prtitions Definition:
More informationCalculus I-II Review Sheet
Clculus I-II Review Sheet 1 Definitions 1.1 Functions A function is f is incresing on n intervl if x y implies f(x) f(y), nd decresing if x y implies f(x) f(y). It is clled monotonic if it is either incresing
More informationUnit Six AP Calculus Unit 6 Review Definite Integrals. Name Period Date NON-CALCULATOR SECTION
Unit Six AP Clculus Unit 6 Review Definite Integrls Nme Period Dte NON-CALCULATOR SECTION Voculry: Directions Define ech word nd give n exmple. 1. Definite Integrl. Men Vlue Theorem (for definite integrls)
More informationSection Areas and Distances. Example 1: Suppose a car travels at a constant 50 miles per hour for 2 hours. What is the total distance traveled?
Section 5. - Ares nd Distnces Exmple : Suppose cr trvels t constnt 5 miles per hour for 2 hours. Wht is the totl distnce trveled? Exmple 2: Suppose cr trvels 75 miles per hour for the first hour, 7 miles
More informationChapter 5. Numerical Integration
Chpter 5. Numericl Integrtion These re just summries of the lecture notes, nd few detils re included. Most of wht we include here is to be found in more detil in Anton. 5. Remrk. There re two topics with
More informationROB EBY Blinn College Mathematics Department
ROB EBY Blinn College Mthemtics Deprtment Mthemtics Deprtment 5.1, 5.2 Are, Definite Integrls MATH 2413 Rob Eby-Fll 26 Weknowthtwhengiventhedistncefunction, wecnfindthevelocitytnypointbyfindingthederivtiveorinstntneous
More information4.4 Areas, Integrals and Antiderivatives
. res, integrls nd ntiderivtives 333. Ares, Integrls nd Antiderivtives This section explores properties of functions defined s res nd exmines some connections mong res, integrls nd ntiderivtives. In order
More informationTaylor Polynomial Inequalities
Tylor Polynomil Inequlities Ben Glin September 17, 24 Abstrct There re instnces where we my wish to pproximte the vlue of complicted function round given point by constructing simpler function such s polynomil
More informationMATH SS124 Sec 39 Concepts summary with examples
This note is mde for students in MTH124 Section 39 to review most(not ll) topics I think we covered in this semester, nd there s exmples fter these concepts, go over this note nd try to solve those exmples
More informationIntegration Techniques
Integrtion Techniques. Integrtion of Trigonometric Functions Exmple. Evlute cos x. Recll tht cos x = cos x. Hence, cos x Exmple. Evlute = ( + cos x) = (x + sin x) + C = x + 4 sin x + C. cos 3 x. Let u
More informationCMDA 4604: Intermediate Topics in Mathematical Modeling Lecture 19: Interpolation and Quadrature
CMDA 4604: Intermedite Topics in Mthemticl Modeling Lecture 19: Interpoltion nd Qudrture In this lecture we mke brief diversion into the res of interpoltion nd qudrture. Given function f C[, b], we sy
More information5 Accumulated Change: The Definite Integral
5 Accumulted Chnge: The Definite Integrl 5.1 Distnce nd Accumulted Chnge * How To Mesure Distnce Trveled nd Visulize Distnce on the Velocity Grph Distnce = Velocity Time Exmple 1 Suppose tht you trvel
More informationMath 113 Exam 2 Practice
Mth 3 Exm Prctice Februry 8, 03 Exm will cover 7.4, 7.5, 7.7, 7.8, 8.-3 nd 8.5. Plese note tht integrtion skills lerned in erlier sections will still be needed for the mteril in 7.5, 7.8 nd chpter 8. This
More informationThe Definite Integral
CHAPTER 3 The Definite Integrl Key Words nd Concepts: Definite Integrl Questions to Consider: How do we use slicing to turn problem sttement into definite integrl? How re definite nd indefinite integrls
More information2 b. , a. area is S= 2π xds. Again, understand where these formulas came from (pages ).
AP Clculus BC Review Chpter 8 Prt nd Chpter 9 Things to Know nd Be Ale to Do Know everything from the first prt of Chpter 8 Given n integrnd figure out how to ntidifferentite it using ny of the following
More informationAB Calculus Review Sheet
AB Clculus Review Sheet Legend: A Preclculus, B Limits, C Differentil Clculus, D Applictions of Differentil Clculus, E Integrl Clculus, F Applictions of Integrl Clculus, G Prticle Motion nd Rtes This is
More informationBest Approximation. Chapter The General Case
Chpter 4 Best Approximtion 4.1 The Generl Cse In the previous chpter, we hve seen how n interpolting polynomil cn be used s n pproximtion to given function. We now wnt to find the best pproximtion to given
More informationIf u = g(x) is a differentiable function whose range is an interval I and f is continuous on I, then f(g(x))g (x) dx = f(u) du
Integrtion by Substitution: The Fundmentl Theorem of Clculus demonstrted the importnce of being ble to find nti-derivtives. We now introduce some methods for finding ntiderivtives: If u = g(x) is differentible
More informationMath 116 Calculus II
Mth 6 Clculus II Contents 5 Exponentil nd Logrithmic functions 5. Review........................................... 5.. Exponentil functions............................... 5.. Logrithmic functions...............................
More information5: The Definite Integral
5: The Definite Integrl 5.: Estimting with Finite Sums Consider moving oject its velocity (meters per second) t ny time (seconds) is given y v t = t+. Cn we use this informtion to determine the distnce
More informationf(x)dx . Show that there 1, 0 < x 1 does not exist a differentiable function g : [ 1, 1] R such that g (x) = f(x) for all
3 Definite Integrl 3.1 Introduction In school one comes cross the definition of the integrl of rel vlued function defined on closed nd bounded intervl [, b] between the limits nd b, i.e., f(x)dx s the
More information( ) as a fraction. Determine location of the highest
AB Clculus Exm Review Sheet - Solutions A. Preclculus Type prolems A1 A2 A3 A4 A5 A6 A7 This is wht you think of doing Find the zeros of f ( x). Set function equl to 0. Fctor or use qudrtic eqution if
More informationPolynomial Approximations for the Natural Logarithm and Arctangent Functions. Math 230
Polynomil Approimtions for the Nturl Logrithm nd Arctngent Functions Mth 23 You recll from first semester clculus how one cn use the derivtive to find n eqution for the tngent line to function t given
More informationSUMMER KNOWHOW STUDY AND LEARNING CENTRE
SUMMER KNOWHOW STUDY AND LEARNING CENTRE Indices & Logrithms 2 Contents Indices.2 Frctionl Indices.4 Logrithms 6 Exponentil equtions. Simplifying Surds 13 Opertions on Surds..16 Scientific Nottion..18
More information( ) where f ( x ) is a. AB Calculus Exam Review Sheet. A. Precalculus Type problems. Find the zeros of f ( x).
AB Clculus Exm Review Sheet A. Preclculus Type prolems A1 Find the zeros of f ( x). This is wht you think of doing A2 A3 Find the intersection of f ( x) nd g( x). Show tht f ( x) is even. A4 Show tht f
More informationUNIFORM CONVERGENCE. Contents 1. Uniform Convergence 1 2. Properties of uniform convergence 3
UNIFORM CONVERGENCE Contents 1. Uniform Convergence 1 2. Properties of uniform convergence 3 Suppose f n : Ω R or f n : Ω C is sequence of rel or complex functions, nd f n f s n in some sense. Furthermore,
More information38 Riemann sums and existence of the definite integral.
38 Riemnn sums nd existence of the definite integrl. In the clcultion of the re of the region X bounded by the grph of g(x) = x 2, the x-xis nd 0 x b, two sums ppered: ( n (k 1) 2) b 3 n 3 re(x) ( n These
More informationLecture 3 ( ) (translated and slightly adapted from lecture notes by Martin Klazar)
Lecture 3 (5.3.2018) (trnslted nd slightly dpted from lecture notes by Mrtin Klzr) Riemnn integrl Now we define precisely the concept of the re, in prticulr, the re of figure U(, b, f) under the grph of
More information