Integrals of Functions of Several Variables

Size: px
Start display at page:

Download "Integrals of Functions of Several Variables"

Transcription

1 Itegrals of Fuctios of Several Variables We ofte resort to itegratios i order to deterie the exact value I of soe quatity which we are uable to evaluate by perforig a fiite uber of additio or ultiplicatio operatios. For exaple, we have to evaluate a itegral to fid the area of the regio betwee the graph of fx) = x + 3 ad the iterval 0,. The itegral is x + 3 ) dx 1) 0 We caot deterie this area by calculatig the areas of a fiite uber of rectagles or triagles because the regio is ot etirely eclosed by straight lie segets. I geeral, a itegratio proble ivolves the followig basic ites: 1. Soe quatity I whose exact value we ust deterie, but we caot calculate it by perforig a fiite uber of additios/ultiplicatios.. Soe set S that has a legth, if it is a subset of the real lie R, a area if it is a subset of the plae, or a volue if it is a subset of 3-diecsioal space. A geeral ter for the legth or the area or the volue of a set S is a easure of S. It should be possible to divide S ito a fiite uber of "saller segets" S 1, S,..., S, to be called "eleets of S", which also have easures. I the itegral 1), the set S is the iterval 0,, with legth. We ca subdivide it ito saller subitervals, e.g. equal subitervals of legth l = each. The sybol l is proouced "delta l" which you should thik of as a "sall legth". 3. Soe fuctio f defied o S such that the product of the easure of a eleet S i ad the value of f at soe poit x i S i gives a reasoable estiate of the cotributio of the eleet S i to the exact value I we wish to deterie. I the itegral 1), the fuctio is fx) = x + 3. If we divide S = 0, ito saller subitervals of legth l = each ad pick a poit x i i a eleet S i = i, i+1) the the product fx i ) l gives a approxiate value of the area eclosed by the seget S i ad the graph of f. Area betwee seget S i ad the graph of f. Approxiatig area Evaluatig the itegral boils dow to doig the followig: Slice S ito a fiite uber of saller eleets S i. Multiply the easure of each eleet S i by the value of f at soe poit x i i the eleet to get a estiate of the cotributio of S i to the value of I. Add up all these cotributios to get a estiate of the value of I. Deterie the liit of all such sus as the easures of the eleets shrik to zero. If the liit it exists, it is by defiitio, the exact value of I ad it is called the itegral of f over S. 1

2 We pla to deote a subset of R, the plae by), R ad a subset of R 3, 3-diesioal space), by B or V. Exaple 1 Let R be the rectagle with vertices at 0,, 0), 5,, 0), 5, 4, 0), 0, 4, 0) ad f be the fuctio of two variables with forula fx, y) = xy + 5. We wish to deterie the volue of the solid, show below), eclosed by the graph of f ad the rectagle. 0,,0) 0,4,0) 5,,0) 5,4,0) We kow how to calculate the volue of ay rectagular box, siply ultiply its legth, width ad height), but this is ot oe of the, therefore we have to "itegrate". More precisely, we have to partitio the rectagle R ito saller rectagles, use the saller rectagles to calculate approxiate values of the required volue the deterie the liit of the approxiatios. The easiest way to partitio R ito saller rectagles is to divide the itervals 0, 5 ad, 4 ito saller subitervals. I the figure below, we divided 0, 5 ito two equal subitervals usig the poits x 0 = 0, x 1 =.5, x = 5 ad, 4 ito 3 equal subitervals usig poits y 0 =, y 1 = 0, y =, y 3 = 4. They partitio R ito 6 saller rectagles R ij = {x, y) : x i x x i+1 ad y j y y j+1, i = 0 or 1 ad j = 0, 1, or. R is partitioed ito saller rectagles.

3 Each oe of these saller rectagles deteries a sall portio of the give solid, show below). The saller solids geerated by the saller rectagles Sice we kow how to calculate volues of rectagular boxes, we approxiate each of the above sall solids with a box that has the sae base ad a suitable height. To siplify the coputatio, we chose to approxiate the sall solid above the rectagle R ij by the box with base R ij ad height fx i, y j ). I geeral, ay poit s i, t j ) i R ij ay be used to get the height of a approxiatig box.) The box approxiatig the solid above R 11 is shaded i the figure below. It has volue.5 fx 1, y 1 ) =.5 f.5, 0) = 15 The total volue of the 6 approxiatig boxes is.5 f0, ) + f0, 0) + f0, ) + f.5, ) + f.5, 0) + f.5, ) = = Therefore Volue of solid I geeral, we ay divide the iterval 0, 5 ito saller subitervals 0, 5, 5, 10,..., 5i, 5i+1),..., 5 1), 5 of equal legth x = 5, to siplify coputatios), ad divide, 4 ito saller subitervals, + 6, + 6, + 1,..., + 6j, + 6j+1),..., + 6 1), 6 of 3

4 equal legth y = 6, the for the rectagles { R ij = x, y) : 5i x 5i+1) ad + 6j 6j+1) y +, i = 0,..., 1 ad j = 0,..., 1 They are of the ad each oe has area A ij = x y. Deote by P ij the sall solid eclosed by the graph of f ad the rectagle R ij. Sice we kow how to calculate volues of boxes, we approxiate it with a box that has the sae base R ij ad height f, + ). Its volue is f ) 5i, + Aij = + 6j ) = + ) The su of these volues is 1 1 f ), + Rij = 1 1 Therefore the required volue is approxiately equal to 1 By defiitio, = =. Secodly, {{ 1 = i) 1 ter s 300 1) = 1 I case you are puzzled, we ade use of the idetity i = 1 1 i=1 j=1 = = i) 1 j 900 ) ) 1) 1) Therefore the volue of the solid is approxiately equal to + ) = ) 300 = ). 1). Fially, = ) 1 1 ) ) ) 1 1 ) The liit of this su as the widths x i ad legths y j of the rectagles R ij shrik to 0 is This ust be the volue of the solid ) + 5 1) 1) = 85 We take this opportuity to itroduce soe otatios ad teriology. The su 1 1 f ), + Rij = is called a Riea su of f deteried by the rectagles { R ij = x, y) : 5i x 5i+1) ad + 6j 6j+1) y , i = 0,..., 1 ad j = 0,..., 1 4

5 The liit of these Riea sus as all the x i s ad y j s shrik to 0 is called the Riea itegral of f over the set R ad is deoted by fx, y)da. 1 Why two itegral sigs? Because the itegral is the liit of a double suatio R 1 f ), + Aij. Ad why da? Because we partitioed R ito eleets, i this case rectagles), with areas A ij. Riea Itegral of a Fuctio of two variable We ow geeralize the above costructio. To this ed, let fx, y) be a give fuctio of two variables ad R be a set i the plae which we ay assue to be a rectagle. If it is ot a rectagle, siply eclose it i a suitable rectagle R ad defie f to have value zero outside R. Divide the rectagle ito saller rectagles R ij which we ay assue, for siplicity, to have the sae legth x ad the sae width y, hece the sae area A ij = x y. Let θ i, α j ) be a poit i the rectagle R ij. The su i=1 j=1 f θ i, α j ) A ij. ) is called a Riea su of f. The liit of these Riea sus as x ad y ted to 0, assuig the liit exists), is called the Riea itegral of f over R ad it is deoted by fx, y)da. R It ay be viewed as the volue of the solid eclosed by the graph of f ad the set R. As explaied i Exaple 1, we use two itegral sigs because we deterie the liit of a double suatio. For this reaso, it is ofte called a double itegral. The sybol da serves to poit out that the set R was divided ito eleets R ij with area A ij. 5

The picture in figure 1.1 helps us to see that the area represents the distance traveled. Figure 1: Area represents distance travelled

The picture in figure 1.1 helps us to see that the area represents the distance traveled. Figure 1: Area represents distance travelled 1 Lecture : Area Area ad distace traveled Approximatig area by rectagles Summatio The area uder a parabola 1.1 Area ad distace Suppose we have the followig iformatio about the velocity of a particle, how

More information

ECE 901 Lecture 4: Estimation of Lipschitz smooth functions

ECE 901 Lecture 4: Estimation of Lipschitz smooth functions ECE 9 Lecture 4: Estiatio of Lipschitz sooth fuctios R. Nowak 5/7/29 Cosider the followig settig. Let Y f (X) + W, where X is a rado variable (r.v.) o X [, ], W is a r.v. o Y R, idepedet of X ad satisfyig

More information

Riemann Sums y = f (x)

Riemann Sums y = f (x) Riema Sums Recall that we have previously discussed the area problem I its simplest form we ca state it this way: The Area Problem Let f be a cotiuous, o-egative fuctio o the closed iterval [a, b] Fid

More information

REVIEW OF CALCULUS Herman J. Bierens Pennsylvania State University (January 28, 2004) x 2., or x 1. x j. ' ' n i'1 x i well.,y 2

REVIEW OF CALCULUS Herman J. Bierens Pennsylvania State University (January 28, 2004) x 2., or x 1. x j. ' ' n i'1 x i well.,y 2 REVIEW OF CALCULUS Hera J. Bieres Pesylvaia State Uiversity (Jauary 28, 2004) 1. Suatio Let x 1,x 2,...,x e a sequece of uers. The su of these uers is usually deoted y x 1 % x 2 %...% x ' j x j, or x 1

More information

Bertrand s postulate Chapter 2

Bertrand s postulate Chapter 2 Bertrad s postulate Chapter We have see that the sequece of prie ubers, 3, 5, 7,... is ifiite. To see that the size of its gaps is ot bouded, let N := 3 5 p deote the product of all prie ubers that are

More information

Bernoulli Polynomials Talks given at LSBU, October and November 2015 Tony Forbes

Bernoulli Polynomials Talks given at LSBU, October and November 2015 Tony Forbes Beroulli Polyoials Tals give at LSBU, October ad Noveber 5 Toy Forbes Beroulli Polyoials The Beroulli polyoials B (x) are defied by B (x), Thus B (x) B (x) ad B (x) x, B (x) x x + 6, B (x) dx,. () B 3

More information

f(1), and so, if f is continuous, f(x) = f(1)x.

f(1), and so, if f is continuous, f(x) = f(1)x. 2.2.35: Let f be a additive fuctio. i Clearly fx = fx ad therefore f x = fx for all Z+ ad x R. Hece, for ay, Z +, f = f, ad so, if f is cotiuous, fx = fx. ii Suppose that f is bouded o soe o-epty ope set.

More information

x !1! + 1!2!

x !1! + 1!2! 4 Euler-Maclauri Suatio Forula 4. Beroulli Nuber & Beroulli Polyoial 4.. Defiitio of Beroulli Nuber Beroulli ubers B (,,3,) are defied as coefficiets of the followig equatio. x e x - B x! 4.. Expreesio

More information

5 3B Numerical Methods for estimating the area of an enclosed region. The Trapezoidal Rule for Approximating the Area Under a Closed Curve

5 3B Numerical Methods for estimating the area of an enclosed region. The Trapezoidal Rule for Approximating the Area Under a Closed Curve 5 3B Numerical Methods for estimatig the area of a eclosed regio The Trapezoidal Rule for Approximatig the Area Uder a Closed Curve The trapezoidal rule requires a closed o a iterval from x = a to x =

More information

Orthogonal Functions

Orthogonal Functions Royal Holloway Uiversity of odo Departet of Physics Orthogoal Fuctios Motivatio Aalogy with vectors You are probably failiar with the cocept of orthogoality fro vectors; two vectors are orthogoal whe they

More information

Solution: APPM 1360 Final Spring 2013

Solution: APPM 1360 Final Spring 2013 APPM 36 Fial Sprig 3. For this proble let the regio R be the regio eclosed by the curve y l( ) ad the lies, y, ad y. (a) (6 pts) Fid the area of the regio R. (b) (6 pts) Suppose the regio R is revolved

More information

Math 21B-B - Homework Set 2

Math 21B-B - Homework Set 2 Math B-B - Homework Set Sectio 5.:. a) lim P k= c k c k ) x k, where P is a partitio of [, 5. x x ) dx b) lim P k= 4 ck x k, where P is a partitio of [,. 4 x dx c) lim P k= ta c k ) x k, where P is a partitio

More information

A PROBABILITY PROBLEM

A PROBABILITY PROBLEM A PROBABILITY PROBLEM A big superarket chai has the followig policy: For every Euros you sped per buy, you ear oe poit (suppose, e.g., that = 3; i this case, if you sped 8.45 Euros, you get two poits,

More information

) is a square matrix with the property that for any m n matrix A, the product AI equals A. The identity matrix has a ii

) is a square matrix with the property that for any m n matrix A, the product AI equals A. The identity matrix has a ii square atrix is oe that has the sae uber of rows as colus; that is, a atrix. he idetity atrix (deoted by I, I, or [] I ) is a square atrix with the property that for ay atrix, the product I equals. he

More information

distinct distinct n k n k n! n n k k n 1 if k n, identical identical p j (k) p 0 if k > n n (k)

distinct distinct n k n k n! n n k k n 1 if k n, identical identical p j (k) p 0 if k > n n (k) THE TWELVEFOLD WAY FOLLOWING GIAN-CARLO ROTA How ay ways ca we distribute objects to recipiets? Equivaletly, we wat to euerate equivalece classes of fuctios f : X Y where X = ad Y = The fuctios are subject

More information

Name Period ALGEBRA II Chapter 1B and 2A Notes Solving Inequalities and Absolute Value / Numbers and Functions

Name Period ALGEBRA II Chapter 1B and 2A Notes Solving Inequalities and Absolute Value / Numbers and Functions Nae Period ALGEBRA II Chapter B ad A Notes Solvig Iequalities ad Absolute Value / Nubers ad Fuctios SECTION.6 Itroductio to Solvig Equatios Objectives: Write ad solve a liear equatio i oe variable. Solve

More information

Now we are looking to find a volume of solid S that lies below a surface z = f(x,y) and R= ab, cd,,[a,b] is the interval over

Now we are looking to find a volume of solid S that lies below a surface z = f(x,y) and R= ab, cd,,[a,b] is the interval over Multiple Itegratio Double Itegrals, Volume, ad Iterated Itegrals I sigle variable calculus we looked to fid the area uder a curve f(x) bouded by the x- axis over some iterval usig summatios the that led

More information

4.1 Sigma Notation and Riemann Sums

4.1 Sigma Notation and Riemann Sums 0 the itegral. Sigma Notatio ad Riema Sums Oe strategy for calculatig the area of a regio is to cut the regio ito simple shapes, calculate the area of each simple shape, ad the add these smaller areas

More information

ECE Spring Prof. David R. Jackson ECE Dept. Notes 20

ECE Spring Prof. David R. Jackson ECE Dept. Notes 20 ECE 6341 Sprig 016 Prof. David R. Jackso ECE Dept. Notes 0 1 Spherical Wave Fuctios Cosider solvig ψ + k ψ = 0 i spherical coordiates z φ θ r y x Spherical Wave Fuctios (cot.) I spherical coordiates we

More information

Math 1314 Lesson 16 Area and Riemann Sums and Lesson 17 Riemann Sums Using GeoGebra; Definite Integrals

Math 1314 Lesson 16 Area and Riemann Sums and Lesson 17 Riemann Sums Using GeoGebra; Definite Integrals Math 1314 Lesso 16 Area ad Riema Sums ad Lesso 17 Riema Sums Usig GeoGebra; Defiite Itegrals The secod questio studied i calculus is the area questio. If a regio coforms to a kow formula from geometry,

More information

1.2 AXIOMATIC APPROACH TO PROBABILITY AND PROPERTIES OF PROBABILITY MEASURE 1.2 AXIOMATIC APPROACH TO PROBABILITY AND

1.2 AXIOMATIC APPROACH TO PROBABILITY AND PROPERTIES OF PROBABILITY MEASURE 1.2 AXIOMATIC APPROACH TO PROBABILITY AND NTEL- robability ad Distributios MODULE 1 ROBABILITY LECTURE 2 Topics 1.2 AXIOMATIC AROACH TO ROBABILITY AND ROERTIES OF ROBABILITY MEASURE 1.2.1 Iclusio-Exclusio Forula I the followig sectio we will discuss

More information

Ma 530 Introduction to Power Series

Ma 530 Introduction to Power Series Ma 530 Itroductio to Power Series Please ote that there is material o power series at Visual Calculus. Some of this material was used as part of the presetatio of the topics that follow. What is a Power

More information

5.6 Binomial Multi-section Matching Transformer

5.6 Binomial Multi-section Matching Transformer 4/14/21 5_6 Bioial Multisectio Matchig Trasforers 1/1 5.6 Bioial Multi-sectio Matchig Trasforer Readig Assiget: pp. 246-25 Oe way to axiize badwidth is to costruct a ultisectio Γ f that is axially flat.

More information

Chapter 5.4 Practice Problems

Chapter 5.4 Practice Problems EXPECTED SKILLS: Chapter 5.4 Practice Problems Uderstad ad kow how to evaluate the summatio (sigma) otatio. Be able to use the summatio operatio s basic properties ad formulas. (You do ot eed to memorize

More information

Lecture 10: Bounded Linear Operators and Orthogonality in Hilbert Spaces

Lecture 10: Bounded Linear Operators and Orthogonality in Hilbert Spaces Lecture : Bouded Liear Operators ad Orthogoality i Hilbert Spaces 34 Bouded Liear Operator Let ( X, ), ( Y, ) i i be ored liear vector spaces ad { } X Y The, T is said to be bouded if a real uber c such

More information

18.01 Calculus Jason Starr Fall 2005

18.01 Calculus Jason Starr Fall 2005 Lecture 18. October 5, 005 Homework. Problem Set 5 Part I: (c). Practice Problems. Course Reader: 3G 1, 3G, 3G 4, 3G 5. 1. Approximatig Riema itegrals. Ofte, there is o simpler expressio for the atiderivative

More information

The Binomial Multi- Section Transformer

The Binomial Multi- Section Transformer 4/4/26 The Bioial Multisectio Matchig Trasforer /2 The Bioial Multi- Sectio Trasforer Recall that a ulti-sectio atchig etwork ca be described usig the theory of sall reflectios as: where: ( ω ) = + e +

More information

AVERAGE MARKS SCALING

AVERAGE MARKS SCALING TERTIARY INSTITUTIONS SERVICE CENTRE Level 1, 100 Royal Street East Perth, Wester Australia 6004 Telephoe (08) 9318 8000 Facsiile (08) 95 7050 http://wwwtisceduau/ 1 Itroductio AVERAGE MARKS SCALING I

More information

We have also learned that, thanks to the Central Limit Theorem and the Law of Large Numbers,

We have also learned that, thanks to the Central Limit Theorem and the Law of Large Numbers, Cofidece Itervals III What we kow so far: We have see how to set cofidece itervals for the ea, or expected value, of a oral probability distributio, both whe the variace is kow (usig the stadard oral,

More information

HOMEWORK #10 SOLUTIONS

HOMEWORK #10 SOLUTIONS Math 33 - Aalysis I Sprig 29 HOMEWORK # SOLUTIONS () Prove that the fuctio f(x) = x 3 is (Riema) itegrable o [, ] ad show that x 3 dx = 4. (Without usig formulae for itegratio that you leart i previous

More information

4.1 SIGMA NOTATION AND RIEMANN SUMS

4.1 SIGMA NOTATION AND RIEMANN SUMS .1 Sigma Notatio ad Riema Sums Cotemporary Calculus 1.1 SIGMA NOTATION AND RIEMANN SUMS Oe strategy for calculatig the area of a regio is to cut the regio ito simple shapes, calculate the area of each

More information

The Definite Integral. Day 3 Riemann Sums

The Definite Integral. Day 3 Riemann Sums The Defiite Itegral Day 3 Riema Sums 2 2 1. If x xy y 9, the a vertical taget exists at ( A) 2 3, 3 ( B) 3,2 3 ( C) 2 3, 3 ( D) 3,2 3 ( E) 2 3, 3 2. Use a local lieariazatio for f x 9 ta x about x 0, the

More information

Ma/CS 6a Class 22: Power Series

Ma/CS 6a Class 22: Power Series Ma/CS 6a Class 22: Power Series By Ada Sheffer Power Series Mooial: ax i. Polyoial: a 0 + a 1 x + a 2 x 2 + + a x. Power series: A x = a 0 + a 1 x + a 2 x 2 + Also called foral power series, because we

More information

Area As A Limit & Sigma Notation

Area As A Limit & Sigma Notation Area As A Limit & Sigma Notatio SUGGESTED REFERENCE MATERIAL: As you work through the problems listed below, you should referece Chapter 5.4 of the recommeded textbook (or the equivalet chapter i your

More information

Automated Proofs for Some Stirling Number Identities

Automated Proofs for Some Stirling Number Identities Autoated Proofs for Soe Stirlig Nuber Idetities Mauel Kauers ad Carste Scheider Research Istitute for Sybolic Coputatio Johaes Kepler Uiversity Altebergerstraße 69 A4040 Liz, Austria Subitted: Sep 1, 2007;

More information

X. Perturbation Theory

X. Perturbation Theory X. Perturbatio Theory I perturbatio theory, oe deals with a ailtoia that is coposed Ĥ that is typically exactly solvable of two pieces: a referece part ad a perturbatio ( Ĥ ) that is assued to be sall.

More information

CHAPTER 10 INFINITE SEQUENCES AND SERIES

CHAPTER 10 INFINITE SEQUENCES AND SERIES CHAPTER 10 INFINITE SEQUENCES AND SERIES 10.1 Sequeces 10.2 Ifiite Series 10.3 The Itegral Tests 10.4 Compariso Tests 10.5 The Ratio ad Root Tests 10.6 Alteratig Series: Absolute ad Coditioal Covergece

More information

Chapter 4. Fourier Series

Chapter 4. Fourier Series Chapter 4. Fourier Series At this poit we are ready to ow cosider the caoical equatios. Cosider, for eample the heat equatio u t = u, < (4.) subject to u(, ) = si, u(, t) = u(, t) =. (4.) Here,

More information

Complex Numbers Solutions

Complex Numbers Solutions Complex Numbers Solutios Joseph Zoller February 7, 06 Solutios. (009 AIME I Problem ) There is a complex umber with imagiary part 64 ad a positive iteger such that Fid. [Solutio: 697] 4i + + 4i. 4i 4i

More information

16 Riemann Sums and Integrals

16 Riemann Sums and Integrals 16 Riema Sums ad Itegrals Defiitio: A partitio P of a closed iterval [a, b], (b >a)isasetof 1 distict poits x i (a, b) togetherwitha = x 0 ad b = x, together with the covetio that i>j x i >x j. Defiitio:

More information

Singular Continuous Measures by Michael Pejic 5/14/10

Singular Continuous Measures by Michael Pejic 5/14/10 Sigular Cotiuous Measures by Michael Peic 5/4/0 Prelimiaries Give a set X, a σ-algebra o X is a collectio of subsets of X that cotais X ad ad is closed uder complemetatio ad coutable uios hece, coutable

More information

6 Integers Modulo n. integer k can be written as k = qn + r, with q,r, 0 r b. So any integer.

6 Integers Modulo n. integer k can be written as k = qn + r, with q,r, 0 r b. So any integer. 6 Itegers Modulo I Example 2.3(e), we have defied the cogruece of two itegers a,b with respect to a modulus. Let us recall that a b (mod ) meas a b. We have proved that cogruece is a equivalece relatio

More information

The z-transform. 7.1 Introduction. 7.2 The z-transform Derivation of the z-transform: x[n] = z n LTI system, h[n] z = re j

The z-transform. 7.1 Introduction. 7.2 The z-transform Derivation of the z-transform: x[n] = z n LTI system, h[n] z = re j The -Trasform 7. Itroductio Geeralie the complex siusoidal represetatio offered by DTFT to a represetatio of complex expoetial sigals. Obtai more geeral characteristics for discrete-time LTI systems. 7.

More information

Double Derangement Permutations

Double Derangement Permutations Ope Joural of iscrete Matheatics, 206, 6, 99-04 Published Olie April 206 i SciRes http://wwwscirporg/joural/ojd http://dxdoiorg/04236/ojd2066200 ouble erageet Perutatios Pooya aeshad, Kayar Mirzavaziri

More information

Chapter 9: Numerical Differentiation

Chapter 9: Numerical Differentiation 178 Chapter 9: Numerical Differetiatio Numerical Differetiatio Formulatio of equatios for physical problems ofte ivolve derivatives (rate-of-chage quatities, such as velocity ad acceleratio). Numerical

More information

Lecture 19. Curve fitting I. 1 Introduction. 2 Fitting a constant to measured data

Lecture 19. Curve fitting I. 1 Introduction. 2 Fitting a constant to measured data Lecture 9 Curve fittig I Itroductio Suppose we are preseted with eight poits of easured data (x i, y j ). As show i Fig. o the left, we could represet the uderlyig fuctio of which these data are saples

More information

Ma 4121: Introduction to Lebesgue Integration Solutions to Homework Assignment 5

Ma 4121: Introduction to Lebesgue Integration Solutions to Homework Assignment 5 Ma 42: Itroductio to Lebesgue Itegratio Solutios to Homework Assigmet 5 Prof. Wickerhauser Due Thursday, April th, 23 Please retur your solutios to the istructor by the ed of class o the due date. You

More information

A string of not-so-obvious statements about correlation in the data. (This refers to the mechanical calculation of correlation in the data.

A string of not-so-obvious statements about correlation in the data. (This refers to the mechanical calculation of correlation in the data. STAT-UB.003 NOTES for Wedesday 0.MAY.0 We will use the file JulieApartet.tw. We ll give the regressio of Price o SqFt, show residual versus fitted plot, save residuals ad fitted. Give plot of (Resid, Price,

More information

5.6 Binomial Multi-section Matching Transformer

5.6 Binomial Multi-section Matching Transformer 4/14/2010 5_6 Bioial Multisectio Matchig Trasforers 1/1 5.6 Bioial Multi-sectio Matchig Trasforer Readig Assiget: pp. 246-250 Oe way to axiize badwidth is to costruct a ultisectio Γ f that is axially flat.

More information

Math 105: Review for Final Exam, Part II - SOLUTIONS

Math 105: Review for Final Exam, Part II - SOLUTIONS Math 5: Review for Fial Exam, Part II - SOLUTIONS. Cosider the fuctio f(x) = x 3 lx o the iterval [/e, e ]. (a) Fid the x- ad y-coordiates of ay ad all local extrema ad classify each as a local maximum

More information

19.1 The dictionary problem

19.1 The dictionary problem CS125 Lecture 19 Fall 2016 19.1 The dictioary proble Cosider the followig data structural proble, usually called the dictioary proble. We have a set of ites. Each ite is a (key, value pair. Keys are i

More information

Math 113, Calculus II Winter 2007 Final Exam Solutions

Math 113, Calculus II Winter 2007 Final Exam Solutions Math, Calculus II Witer 7 Fial Exam Solutios (5 poits) Use the limit defiitio of the defiite itegral ad the sum formulas to compute x x + dx The check your aswer usig the Evaluatio Theorem Solutio: I this

More information

8.3 Perturbation theory

8.3 Perturbation theory 8.3 Perturbatio theory Slides: Video 8.3.1 Costructig erturbatio theory Text referece: Quatu Mechaics for Scietists ad gieers Sectio 6.3 (u to First order erturbatio theory ) Perturbatio theory Costructig

More information

Math 176 Calculus Sec. 5.1: Areas and Distances (Using Finite Sums)

Math 176 Calculus Sec. 5.1: Areas and Distances (Using Finite Sums) Math 176 Calculus Sec. 5.1: Areas ad Distaces (Usig Fiite Sums) I. Area A. Cosider the problem of fidig the area uder the curve o the f y=-x 2 +5 over the domai [0, 2]. We ca approximate this area by usig

More information

Define a Markov chain on {1,..., 6} with transition probability matrix P =

Define a Markov chain on {1,..., 6} with transition probability matrix P = Pla Group Work 0. The title says it all Next Tie: MCMC ad Geeral-state Markov Chais Midter Exa: Tuesday 8 March i class Hoework 4 due Thursday Uless otherwise oted, let X be a irreducible, aperiodic Markov

More information

Exponential Functions and Taylor Series

Exponential Functions and Taylor Series MATH 4530: Aalysis Oe Expoetial Fuctios ad Taylor Series James K. Peterso Departmet of Biological Scieces ad Departmet of Mathematical Scieces Clemso Uiversity March 29, 2017 MATH 4530: Aalysis Oe Outlie

More information

The Binomial Multi-Section Transformer

The Binomial Multi-Section Transformer 4/15/2010 The Bioial Multisectio Matchig Trasforer preset.doc 1/24 The Bioial Multi-Sectio Trasforer Recall that a ulti-sectio atchig etwork ca be described usig the theory of sall reflectios as: where:

More information

Math 220A Fall 2007 Homework #2. Will Garner A

Math 220A Fall 2007 Homework #2. Will Garner A Math 0A Fall 007 Homewor # Will Garer Pg 3 #: Show that {cis : a o-egative iteger} is dese i T = {z œ : z = }. For which values of q is {cis(q): a o-egative iteger} dese i T? To show that {cis : a o-egative

More information

REAL ANALYSIS II: PROBLEM SET 1 - SOLUTIONS

REAL ANALYSIS II: PROBLEM SET 1 - SOLUTIONS REAL ANALYSIS II: PROBLEM SET 1 - SOLUTIONS 18th Feb, 016 Defiitio (Lipschitz fuctio). A fuctio f : R R is said to be Lipschitz if there exists a positive real umber c such that for ay x, y i the domai

More information

Data Analysis and Statistical Methods Statistics 651

Data Analysis and Statistical Methods Statistics 651 Data Aalysis ad Statistical Methods Statistics 651 http://www.stat.tau.edu/~suhasii/teachig.htl Suhasii Subba Rao Exaple The itroge cotet of three differet clover plats is give below. 3DOK1 3DOK5 3DOK7

More information

Areas and Distances. We can easily find areas of certain geometric figures using well-known formulas:

Areas and Distances. We can easily find areas of certain geometric figures using well-known formulas: Areas ad Distaces We ca easily fid areas of certai geometric figures usig well-kow formulas: However, it is t easy to fid the area of a regio with curved sides: METHOD: To evaluate the area of the regio

More information

Integrable Functions. { f n } is called a determining sequence for f. If f is integrable with respect to, then f d does exist as a finite real number

Integrable Functions. { f n } is called a determining sequence for f. If f is integrable with respect to, then f d does exist as a finite real number MATH 532 Itegrable Fuctios Dr. Neal, WKU We ow shall defie what it meas for a measurable fuctio to be itegrable, show that all itegral properties of simple fuctios still hold, ad the give some coditios

More information

1 Approximating Integrals using Taylor Polynomials

1 Approximating Integrals using Taylor Polynomials Seughee Ye Ma 8: Week 7 Nov Week 7 Summary This week, we will lear how we ca approximate itegrals usig Taylor series ad umerical methods. Topics Page Approximatig Itegrals usig Taylor Polyomials. Defiitios................................................

More information

The Growth of Functions. Theoretical Supplement

The Growth of Functions. Theoretical Supplement The Growth of Fuctios Theoretical Supplemet The Triagle Iequality The triagle iequality is a algebraic tool that is ofte useful i maipulatig absolute values of fuctios. The triagle iequality says that

More information

Lecture 3 The Lebesgue Integral

Lecture 3 The Lebesgue Integral Lecture 3: The Lebesgue Itegral 1 of 14 Course: Theory of Probability I Term: Fall 2013 Istructor: Gorda Zitkovic Lecture 3 The Lebesgue Itegral The costructio of the itegral Uless expressly specified

More information

Product measures, Tonelli s and Fubini s theorems For use in MAT3400/4400, autumn 2014 Nadia S. Larsen. Version of 13 October 2014.

Product measures, Tonelli s and Fubini s theorems For use in MAT3400/4400, autumn 2014 Nadia S. Larsen. Version of 13 October 2014. Product measures, Toelli s ad Fubii s theorems For use i MAT3400/4400, autum 2014 Nadia S. Larse Versio of 13 October 2014. 1. Costructio of the product measure The purpose of these otes is to preset the

More information

Statistics for Applications Fall Problem Set 7

Statistics for Applications Fall Problem Set 7 18.650. Statistics for Applicatios Fall 016. Proble Set 7 Due Friday, Oct. 8 at 1 oo Proble 1 QQ-plots Recall that the Laplace distributio with paraeter λ > 0 is the cotiuous probaλ bility easure with

More information

Perturbation Theory, Zeeman Effect, Stark Effect

Perturbation Theory, Zeeman Effect, Stark Effect Chapter 8 Perturbatio Theory, Zeea Effect, Stark Effect Ufortuately, apart fro a few siple exaples, the Schrödiger equatio is geerally ot exactly solvable ad we therefore have to rely upo approxiative

More information

ACCESS TO SCIENCE, ENGINEERING AND AGRICULTURE: MATHEMATICS 1 MATH00030 SEMESTER / Statistics

ACCESS TO SCIENCE, ENGINEERING AND AGRICULTURE: MATHEMATICS 1 MATH00030 SEMESTER / Statistics ACCESS TO SCIENCE, ENGINEERING AND AGRICULTURE: MATHEMATICS 1 MATH00030 SEMESTER 1 018/019 DR. ANTHONY BROWN 8. Statistics 8.1. Measures of Cetre: Mea, Media ad Mode. If we have a series of umbers the

More information

Riemann Hypothesis Proof

Riemann Hypothesis Proof Riea Hypothesis Proof H. Vic Dao 43 rd West Coast Nuber Theory Coferece, Dec 6-0, 009, Asiloar, CA. Revised 0/8/00. Riea Hypothesis Proof H. Vic Dao vic0@cocast.et March, 009 Revised Deceber, 009 Abstract

More information

Lecture 6: Integration and the Mean Value Theorem. slope =

Lecture 6: Integration and the Mean Value Theorem. slope = Math 8 Istructor: Padraic Bartlett Lecture 6: Itegratio ad the Mea Value Theorem Week 6 Caltech 202 The Mea Value Theorem The Mea Value Theorem abbreviated MVT is the followig result: Theorem. Suppose

More information

A PROOF OF THE THUE-SIEGEL THEOREM ABOUT THE APPROXIMATION OF ALGEBRAIC NUMBERS FOR BINOMIAL EQUATIONS

A PROOF OF THE THUE-SIEGEL THEOREM ABOUT THE APPROXIMATION OF ALGEBRAIC NUMBERS FOR BINOMIAL EQUATIONS A PROO O THE THUE-SIEGEL THEOREM ABOUT THE APPROXIMATION O ALGEBRAIC NUMBERS OR BINOMIAL EQUATIONS KURT MAHLER, TRANSLATED BY KARL LEVY I 98 Thue () showed that algebraic ubers of the special for = p a

More information

Answer Key, Problem Set 1, Written

Answer Key, Problem Set 1, Written Cheistry 1 Mies, Sprig, 018 Aswer Key, Proble Set 1, Writte 1. 14.3;. 14.34 (add part (e): Estiate / calculate the iitial rate of the reactio); 3. NT1; 4. NT; 5. 14.37; 6. 14.39; 7. 14.41; 8. NT3; 9. 14.46;

More information

Math 155 (Lecture 3)

Math 155 (Lecture 3) Math 55 (Lecture 3) September 8, I this lecture, we ll cosider the aswer to oe of the most basic coutig problems i combiatorics Questio How may ways are there to choose a -elemet subset of the set {,,,

More information

Lecture 2: Monte Carlo Simulation

Lecture 2: Monte Carlo Simulation STAT/Q SCI 43: Itroductio to Resamplig ethods Sprig 27 Istructor: Ye-Chi Che Lecture 2: ote Carlo Simulatio 2 ote Carlo Itegratio Assume we wat to evaluate the followig itegratio: e x3 dx What ca we do?

More information

September 2012 C1 Note. C1 Notes (Edexcel) Copyright - For AS, A2 notes and IGCSE / GCSE worksheets 1

September 2012 C1 Note. C1 Notes (Edexcel) Copyright   - For AS, A2 notes and IGCSE / GCSE worksheets 1 September 0 s (Edecel) Copyright www.pgmaths.co.uk - For AS, A otes ad IGCSE / GCSE worksheets September 0 Copyright www.pgmaths.co.uk - For AS, A otes ad IGCSE / GCSE worksheets September 0 Copyright

More information

Integrals, areas, Riemann sums

Integrals, areas, Riemann sums Itegrals, areas, Riema sums October 5, 2017 Itegrals, areas, Riema sums We had the ith breakfast yesterday morig: There are still lots of slots available Breakfast #10, ext Moday (October 9) at 9AM. Itegrals,

More information

(s)h(s) = K( s + 8 ) = 5 and one finite zero is located at z 1

(s)h(s) = K( s + 8 ) = 5 and one finite zero is located at z 1 ROOT LOCUS TECHNIQUE 93 should be desiged differetly to eet differet specificatios depedig o its area of applicatio. We have observed i Sectio 6.4 of Chapter 6, how the variatio of a sigle paraeter like

More information

Exponential Functions and Taylor Series

Exponential Functions and Taylor Series Expoetial Fuctios ad Taylor Series James K. Peterso Departmet of Biological Scieces ad Departmet of Mathematical Scieces Clemso Uiversity March 29, 207 Outlie Revistig the Expoetial Fuctio Taylor Series

More information

Infinite Sequences and Series

Infinite Sequences and Series Chapter 6 Ifiite Sequeces ad Series 6.1 Ifiite Sequeces 6.1.1 Elemetary Cocepts Simply speakig, a sequece is a ordered list of umbers writte: {a 1, a 2, a 3,...a, a +1,...} where the elemets a i represet

More information

Discrete Mathematics: Lectures 8 and 9 Principle of Inclusion and Exclusion Instructor: Arijit Bishnu Date: August 11 and 13, 2009

Discrete Mathematics: Lectures 8 and 9 Principle of Inclusion and Exclusion Instructor: Arijit Bishnu Date: August 11 and 13, 2009 Discrete Matheatics: Lectures 8 ad 9 Priciple of Iclusio ad Exclusio Istructor: Arijit Bishu Date: August ad 3, 009 As you ca observe by ow, we ca cout i various ways. Oe such ethod is the age-old priciple

More information

Summer MA Lesson 13 Section 1.6, Section 1.7 (part 1)

Summer MA Lesson 13 Section 1.6, Section 1.7 (part 1) Suer MA 1500 Lesso 1 Sectio 1.6, Sectio 1.7 (part 1) I Solvig Polyoial Equatios Liear equatio ad quadratic equatios of 1 variable are specific types of polyoial equatios. Soe polyoial equatios of a higher

More information

Recitation 4: Lagrange Multipliers and Integration

Recitation 4: Lagrange Multipliers and Integration Math 1c TA: Padraic Bartlett Recitatio 4: Lagrage Multipliers ad Itegratio Week 4 Caltech 211 1 Radom Questio Hey! So, this radom questio is pretty tightly tied to today s lecture ad the cocept of cotet

More information

Series III. Chapter Alternating Series

Series III. Chapter Alternating Series Chapter 9 Series III With the exceptio of the Null Sequece Test, all the tests for series covergece ad divergece that we have cosidered so far have dealt oly with series of oegative terms. Series with

More information

Review Problems for the Final

Review Problems for the Final Review Problems for the Fial Math - 3 7 These problems are provided to help you study The presece of a problem o this hadout does ot imply that there will be a similar problem o the test Ad the absece

More information

The second is the wish that if f is a reasonably nice function in E and φ n

The second is the wish that if f is a reasonably nice function in E and φ n 8 Sectio : Approximatios i Reproducig Kerel Hilbert Spaces I this sectio, we address two cocepts. Oe is the wish that if {E, } is a ierproduct space of real valued fuctios o the iterval [,], the there

More information

6.4 Binomial Coefficients

6.4 Binomial Coefficients 64 Bioial Coefficiets Pascal s Forula Pascal s forula, aed after the seveteeth-cetury Frech atheaticia ad philosopher Blaise Pascal, is oe of the ost faous ad useful i cobiatorics (which is the foral ter

More information

Solutions to quizzes Math Spring 2007

Solutions to quizzes Math Spring 2007 to quizzes Math 4- Sprig 7 Name: Sectio:. Quiz a) x + x dx b) l x dx a) x + dx x x / + x / dx (/3)x 3/ + x / + c. b) Set u l x, dv dx. The du /x ad v x. By Itegratio by Parts, x(/x)dx x l x x + c. l x

More information

arxiv: v1 [math.st] 12 Dec 2018

arxiv: v1 [math.st] 12 Dec 2018 DIVERGENCE MEASURES ESTIMATION AND ITS ASYMPTOTIC NORMALITY THEORY : DISCRETE CASE arxiv:181.04795v1 [ath.st] 1 Dec 018 Abstract. 1) BA AMADOU DIADIÉ AND 1,,4) LO GANE SAMB 1. Itroductio 1.1. Motivatios.

More information

Section 13.3 Area and the Definite Integral

Section 13.3 Area and the Definite Integral Sectio 3.3 Area ad the Defiite Itegral We ca easily fid areas of certai geometric figures usig well-kow formulas: However, it is t easy to fid the area of a regio with curved sides: METHOD: To evaluate

More information

7 Sequences of real numbers

7 Sequences of real numbers 40 7 Sequeces of real umbers 7. Defiitios ad examples Defiitio 7... A sequece of real umbers is a real fuctio whose domai is the set N of atural umbers. Let s : N R be a sequece. The the values of s are

More information

9.3 Power Series: Taylor & Maclaurin Series

9.3 Power Series: Taylor & Maclaurin Series 9.3 Power Series: Taylor & Maclauri Series If is a variable, the a ifiite series of the form 0 is called a power series (cetered at 0 ). a a a a a 0 1 0 is a power series cetered at a c a a c a c a c 0

More information

Discrete-Time Systems, LTI Systems, and Discrete-Time Convolution

Discrete-Time Systems, LTI Systems, and Discrete-Time Convolution EEL5: Discrete-Time Sigals ad Systems. Itroductio I this set of otes, we begi our mathematical treatmet of discrete-time s. As show i Figure, a discrete-time operates or trasforms some iput sequece x [

More information

A GENERALIZED BERNSTEIN APPROXIMATION THEOREM

A GENERALIZED BERNSTEIN APPROXIMATION THEOREM Ø Ñ Å Ø Ñ Ø Ð ÈÙ Ð Ø ÓÒ DOI: 10.2478/v10127-011-0029-x Tatra Mt. Math. Publ. 49 2011, 99 109 A GENERALIZED BERNSTEIN APPROXIMATION THEOREM Miloslav Duchoň ABSTRACT. The preset paper is cocered with soe

More information

For example suppose we divide the interval [0,2] into 5 equal subintervals of length

For example suppose we divide the interval [0,2] into 5 equal subintervals of length Math 1206 Calculus Sec 1: Estimatig with Fiite Sums Abbreviatios: wrt with respect to! for all! there exists! therefore Def defiitio Th m Theorem sol solutio! perpedicular iff or! if ad oly if pt poit

More information

INFINITE SEQUENCES AND SERIES

INFINITE SEQUENCES AND SERIES INFINITE SEQUENCES AND SERIES INFINITE SEQUENCES AND SERIES I geeral, it is difficult to fid the exact sum of a series. We were able to accomplish this for geometric series ad the series /[(+)]. This is

More information

MA131 - Analysis 1. Workbook 9 Series III

MA131 - Analysis 1. Workbook 9 Series III MA3 - Aalysis Workbook 9 Series III Autum 004 Cotets 4.4 Series with Positive ad Negative Terms.............. 4.5 Alteratig Series.......................... 4.6 Geeral Series.............................

More information

Question 1: The magnetic case

Question 1: The magnetic case September 6, 018 Corell Uiversity, Departmet of Physics PHYS 337, Advace E&M, HW # 4, due: 9/19/018, 11:15 AM Questio 1: The magetic case I class, we skipped over some details, so here you are asked to

More information

Calculus II exam 1 6/18/07 All problems are worth 10 points unless otherwise noted. Show all analytic work.

Calculus II exam 1 6/18/07 All problems are worth 10 points unless otherwise noted. Show all analytic work. 9.-0 Calculus II exam 6/8/07 All problems are worth 0 poits uless otherwise oted. Show all aalytic work.. (5 poits) Prove that the area eclosed i the circle. f( x) = x +, 0 x. Use the approximate the area

More information

6.3 Testing Series With Positive Terms

6.3 Testing Series With Positive Terms 6.3. TESTING SERIES WITH POSITIVE TERMS 307 6.3 Testig Series With Positive Terms 6.3. Review of what is kow up to ow I theory, testig a series a i for covergece amouts to fidig the i= sequece of partial

More information