Fitting a Polynomial to Heat Capacity as a Function of Temperature for Ag. Mathematical Background Document

Size: px
Start display at page:

Download "Fitting a Polynomial to Heat Capacity as a Function of Temperature for Ag. Mathematical Background Document"

Transcription

1 Fttng Polynol to Het Cpcty s Functon of Teperture for Ag. thetcl Bckground Docuent by Theres Jul Zelnsk Deprtent of Chestry, edcl Technology, nd Physcs onouth Unversty West ong Brnch, J tzelns@onouth.edu Theres Jul Zelnsk, 996, 997, 998. You re welcoe to use ths docuent n your own clsses but coercl use s not llowed wthout the persson of the uthor. Fttng thetcl functon to experentl dt s useful technque for representng dt wth n nlytcl functon. To do ths we need to dentfy the type of functon nd procedure for optzng the fttng preters n the functon. Polynol expressons y be sutble choce n ny cses. Polynols lso provde n esy begnnng for exnng the bsc procedure for fttng functon to set of dt. The obectve s to choose polynol expresson such tht the su of the squres of the devtons between the functon nd the dt re nzed. Here we wll use the flr lest squres procedure tht ost students lern bout n the physcl chestry lbortory. The thetcs for ths s reltvely strght forwrd nd cn be found n ost physcl chestry texts or lbortory nuls. Consder polynol f ( x) x x x x () where,,, up to re the fttng preters, nd s the order of the polynol. If you hve set of dt consstng of x nd y vlues, then you cn clculte n f(x) for ech x vlue,.e. f(x ). The f(x ) cn then be copred to the y vlues. If the f(x ) nd y gree for every x then you hve functon f(x) tht fts the dt. We use sttstcs to deterne the degree of goodnes of ths ft. A frst pproch s to use the ethod of lest squres. Ths s the ethod tht wll be developed n these notes. Exercse : For qudrtc functon the coeffcents re.5,., nd -4.5x -4. Copute f(x ) for the followng prs of x, y dt: 3, 4.8; 5,.7; 7, 6.3; 9, 9.. The ethod of lest squres requres tht the su of the squres of the devtons,.e. squre of the resduls, be nzed. Ths s defned s: [ ] R y f( x ) () where f(x ) s the vlue of f(x) for dt pont nd there re dt ponts n the experentl set. The experentl dt re tbulted n prs of x nd y vlues. f(x ) s the coputed vlue of the property y nd t s copred to the experentl vlue y to obtn the resdul. R s the resdul functon. It s the su of the squres of the devtons nd s soetes clled SSD n thcd docuents. It doesn t tke Creted: Februry 996 fttng.doc Author: Theres Jul Zelnsk odfed: July, 998 Pge

2 long to get used to the for of ths functon so tht you wll be ble to recognze t no tter wht ne s hs. The dscusson tht follows does not consder the experentl weght of the dt ponts y. Exercse : Copute R for the dt n Exercse.. nzton of the resduls s ccoplshed by stndrd pplcton of clculus. We wnt to fnd the best set of fttng preters, nely those whch nze R. Therefore we tke the dervtve wth respect to ech fttng preter nd set t equl to zero s shown n equton 3.,,, etc. (3) The result s set of sultneous equtons, one for ech coeffcent. Soe of these equtons re: ( y x x ) ( ) x x ( ) x x (4) where there s one equton for ech fttng preter,.e. equtons becuse the powers of x rnge fro to n the polynol. The suton s tken over the,, 3, dt ponts. In thcd ths y pper s,,, 3. - dependng on how the rry nuberng s set n the docuent you re usng. Exercse 3: Show tht the equtons n (4) coe fro the equtons n (3). Rerrngng (4) gves: ( x x ) 3 ( x x x ) 3 ( ) y y x x x x y x 4 (5) Systes of lner equtons lke ths re best represented by trx notton. Creted: Februry 996 fttng.doc Author: Theres Jul Zelnsk odfed: July, 998 Pge

3 Creted: Februry 996 fttng.doc Author: Theres Jul Zelnsk odfed: July, 998 Pge 3 A b (6) otce the bold font on the coponents of equton (6). Ths ndctes tht these re trces. trx A s squre syetrc rel trx. b nd re colun vectors. We see ther explct for here n equtons 7 nd 8. Proble: Check your skll wth trx npultons by showng tht the trx equton (6) corresponds to representton of the set of sultneous equtons shown n equton (5). Hnt: use the trx nd vectors n equton (7) nd (8). A 3 (7) nd b y (8) The eleents n trx A re esly wrtten by usng the followng expresson:

4 A,k ( x ) ( x ) k (9) where s the row nd k s the colun. nd k correspond to the subscrpt of the coeffcent used n the polynol expresson. Do not confuse ths wth the rnge nteger,, tht dentfes the dt ponts. nd k rnge fro to,.e. over the totl nuber of fttng preters. The defult ntl ndex for vectors nd rrys s zero n thcd. If our dt were represented n ths defult then would lso run fro to - nd the trx n equton (7) nd the vectors n equton (8) would need to be rewrtten. It s portnt to be flexble but ccurte wth our use of the rnge vrble. In lke fshon we wrte the vector b n equton () ( ) () b y x where b s row eleent n the colun vector b. There re eleents n the vector b nd eleents n the vector. The trx A s by squre. Through trx lgebr we cn solve for the vector A. Be creful bout how you ultply trces. A - A A b A b () The vector contns ll of the fttng preters n the polynol expnson. We obtn the vrnce of the ft nd the vrnce of the fttng preters by: R σ σ σ A () where,,... nd R s the su of the squres of the devtons t the end of the fttng process. Queston : Wht crter would you use to deterne whch polynol you would choose to represent set of dt? The docuent Slver.cd s thcd pleentton of polynol curve fttng. Ths docuent, the thcd docuent, nd sple dt re t the thcd WWW ste or dskette provded by your nstructor. The thcd docuent shows vrous opertons but you should frst experent wth vryng the order of the polynol nd observng the ft of the functon to the dt. Record your observtons n your note book. After you hve deonstrted copetence wth the requred obectves of ths lesson you Creted: Februry 996 fttng.doc Author: Theres Jul Zelnsk odfed: July, 998 Pge 4

5 ght lke to try other sets of dt or functons to lern ore bout curve fttng. Other thcd docuents on the WWW ste deonstrte lterntve curve fttng pproches. Queston : How does the goodness of ft prove wth ncresng order of the fttng polynol? Queston 3: How does one choose the best polynol to represent the dt? Queston 4: Use your textbook or nother text to copre the functons used to represent the het cpcty of terls s functon of teperture. Queston 5: Wht s the crter would you use for choosng to use one functon or nother to use when fttng polynol to het cpcty dt? References: Johnson, K. Jeffrey, uercl ethods n Chestry ; ew York: rcel Dekker, Inc., 98. Bevngton, Phlp R., Dt Reducton nd Error Anlyss for the Physcl Scences ; ew York: cgrw Hll Book Copny, 969. Hng, R. W., uercl ethods for Scentsts nd Engneers, nd Ed.;ew York: Dover Publctons, 986. Acknowledgent: Prtl support for ths work ws provded to TJZ by the tonl Scence Foundton's Dvson of Undergrdute Educton through grnt DUE # nd by the ew Trdtons proect t the Unversty of Wsconsn - dson through the tonl Scence Foundton's Dvson of Undergrdute Educton through grnt DUE # Creted: Februry 996 fttng.doc Author: Theres Jul Zelnsk odfed: July, 998 Pge 5

Rank One Update And the Google Matrix by Al Bernstein Signal Science, LLC

Rank One Update And the Google Matrix by Al Bernstein Signal Science, LLC Introducton Rnk One Updte And the Google Mtrx y Al Bernsten Sgnl Scence, LLC www.sgnlscence.net here re two dfferent wys to perform mtrx multplctons. he frst uses dot product formulton nd the second uses

More information

Lecture 4: Piecewise Cubic Interpolation

Lecture 4: Piecewise Cubic Interpolation Lecture notes on Vrtonl nd Approxmte Methods n Appled Mthemtcs - A Perce UBC Lecture 4: Pecewse Cubc Interpolton Compled 6 August 7 In ths lecture we consder pecewse cubc nterpolton n whch cubc polynoml

More information

Solubilities and Thermodynamic Properties of SO 2 in Ionic

Solubilities and Thermodynamic Properties of SO 2 in Ionic Solubltes nd Therodync Propertes of SO n Ionc Lquds Men Jn, Yucu Hou, b Weze Wu, *, Shuhng Ren nd Shdong Tn, L Xo, nd Zhgng Le Stte Key Lbortory of Checl Resource Engneerng, Beng Unversty of Checl Technology,

More information

Applied Statistics Qualifier Examination

Applied Statistics Qualifier Examination Appled Sttstcs Qulfer Exmnton Qul_june_8 Fll 8 Instructons: () The exmnton contns 4 Questons. You re to nswer 3 out of 4 of them. () You my use ny books nd clss notes tht you mght fnd helpful n solvng

More information

DCDM BUSINESS SCHOOL NUMERICAL METHODS (COS 233-8) Solutions to Assignment 3. x f(x)

DCDM BUSINESS SCHOOL NUMERICAL METHODS (COS 233-8) Solutions to Assignment 3. x f(x) DCDM BUSINESS SCHOOL NUMEICAL METHODS (COS -8) Solutons to Assgnment Queston Consder the followng dt: 5 f() 8 7 5 () Set up dfference tble through fourth dfferences. (b) Wht s the mnmum degree tht n nterpoltng

More information

UNIVERSITY OF IOANNINA DEPARTMENT OF ECONOMICS. M.Sc. in Economics MICROECONOMIC THEORY I. Problem Set II

UNIVERSITY OF IOANNINA DEPARTMENT OF ECONOMICS. M.Sc. in Economics MICROECONOMIC THEORY I. Problem Set II Mcroeconomc Theory I UNIVERSITY OF IOANNINA DEPARTMENT OF ECONOMICS MSc n Economcs MICROECONOMIC THEORY I Techng: A Lptns (Note: The number of ndctes exercse s dffculty level) ()True or flse? If V( y )

More information

INTRODUCTION TO COMPLEX NUMBERS

INTRODUCTION TO COMPLEX NUMBERS INTRODUCTION TO COMPLEX NUMBERS The numers -4, -3, -, -1, 0, 1,, 3, 4 represent the negtve nd postve rel numers termed ntegers. As one frst lerns n mddle school they cn e thought of s unt dstnce spced

More information

Statistics 423 Midterm Examination Winter 2009

Statistics 423 Midterm Examination Winter 2009 Sttstcs 43 Mdterm Exmnton Wnter 009 Nme: e-ml: 1. Plese prnt your nme nd e-ml ddress n the bove spces.. Do not turn ths pge untl nstructed to do so. 3. Ths s closed book exmnton. You my hve your hnd clcultor

More information

6 Roots of Equations: Open Methods

6 Roots of Equations: Open Methods HK Km Slghtly modfed 3//9, /8/6 Frstly wrtten t Mrch 5 6 Roots of Equtons: Open Methods Smple Fed-Pont Iterton Newton-Rphson Secnt Methods MATLAB Functon: fzero Polynomls Cse Study: Ppe Frcton Brcketng

More information

Jens Siebel (University of Applied Sciences Kaiserslautern) An Interactive Introduction to Complex Numbers

Jens Siebel (University of Applied Sciences Kaiserslautern) An Interactive Introduction to Complex Numbers Jens Sebel (Unversty of Appled Scences Kserslutern) An Interctve Introducton to Complex Numbers 1. Introducton We know tht some polynoml equtons do not hve ny solutons on R/. Exmple 1.1: Solve x + 1= for

More information

Quiz: Experimental Physics Lab-I

Quiz: Experimental Physics Lab-I Mxmum Mrks: 18 Totl tme llowed: 35 mn Quz: Expermentl Physcs Lb-I Nme: Roll no: Attempt ll questons. 1. In n experment, bll of mss 100 g s dropped from heght of 65 cm nto the snd contner, the mpct s clled

More information

APPROXIMATE SOLUTION OF HIGHER ORDER LINEAR DIFFERENTIAL EQUATIONS BY MEANS OF A NEW RATIONAL CHEBYSHEV COLLOCATION METHOD

APPROXIMATE SOLUTION OF HIGHER ORDER LINEAR DIFFERENTIAL EQUATIONS BY MEANS OF A NEW RATIONAL CHEBYSHEV COLLOCATION METHOD thetcl nd oputtonl Applctons ol. 5 o. pp. 5-56. Assocton for Scentfc eserch APPOXIAE SOLUIO OF HIGHE ODE LIEA DIFFEEIAL EQUAIOS BY EAS OF A EW AIOAL HEBYSHE OLLOAIO EHOD Slh Ylçınbş * esrn Özso ehet Sezer

More information

Exponents and Powers

Exponents and Powers EXPONENTS AND POWERS 9 Exponents nd Powers CHAPTER. Introduction Do you know? Mss of erth is 5,970,000,000,000, 000, 000, 000, 000 kg. We hve lredy lernt in erlier clss how to write such lrge nubers ore

More information

Principle Component Analysis

Principle Component Analysis Prncple Component Anlyss Jng Go SUNY Bufflo Why Dmensonlty Reducton? We hve too mny dmensons o reson bout or obtn nsghts from o vsulze oo much nose n the dt Need to reduce them to smller set of fctors

More information

CISE 301: Numerical Methods Lecture 5, Topic 4 Least Squares, Curve Fitting

CISE 301: Numerical Methods Lecture 5, Topic 4 Least Squares, Curve Fitting CISE 3: umercl Methods Lecture 5 Topc 4 Lest Squres Curve Fttng Dr. Amr Khouh Term Red Chpter 7 of the tetoo c Khouh CISE3_Topc4_Lest Squre Motvton Gven set of epermentl dt 3 5. 5.9 6.3 The reltonshp etween

More information

Chapter Newton-Raphson Method of Solving a Nonlinear Equation

Chapter Newton-Raphson Method of Solving a Nonlinear Equation Chpter.4 Newton-Rphson Method of Solvng Nonlner Equton After redng ths chpter, you should be ble to:. derve the Newton-Rphson method formul,. develop the lgorthm of the Newton-Rphson method,. use the Newton-Rphson

More information

Lecture 3 Camera Models 2 & Camera Calibration. Professor Silvio Savarese Computational Vision and Geometry Lab

Lecture 3 Camera Models 2 & Camera Calibration. Professor Silvio Savarese Computational Vision and Geometry Lab Lecture Cer Models Cer Clbrton rofessor Slvo Svrese Coputtonl Vson nd Geoetry Lb Slvo Svrese Lecture - Jn 7 th, 8 Lecture Cer Models Cer Clbrton Recp of cer odels Cer clbrton proble Cer clbrton wth rdl

More information

Katholieke Universiteit Leuven Department of Computer Science

Katholieke Universiteit Leuven Department of Computer Science Updte Rules for Weghted Non-negtve FH*G Fctorzton Peter Peers Phlp Dutré Report CW 440, Aprl 006 Ktholeke Unverstet Leuven Deprtment of Computer Scence Celestjnenln 00A B-3001 Heverlee (Belgum) Updte Rules

More information

Chapter 5 Supplemental Text Material R S T. ij i j ij ijk

Chapter 5 Supplemental Text Material R S T. ij i j ij ijk Chpter 5 Supplementl Text Mterl 5-. Expected Men Squres n the Two-fctor Fctorl Consder the two-fctor fxed effects model y = µ + τ + β + ( τβ) + ε k R S T =,,, =,,, k =,,, n gven s Equton (5-) n the textook.

More information

The Number of Rows which Equal Certain Row

The Number of Rows which Equal Certain Row Interntonl Journl of Algebr, Vol 5, 011, no 30, 1481-1488 he Number of Rows whch Equl Certn Row Ahmd Hbl Deprtment of mthemtcs Fcult of Scences Dmscus unverst Dmscus, Sr hblhmd1@gmlcom Abstrct Let be X

More information

Course Review Introduction to Computer Methods

Course Review Introduction to Computer Methods Course Revew Wht you hopefully hve lerned:. How to nvgte nsde MIT computer system: Athen, UNIX, emcs etc. (GCR). Generl des bout progrmmng (GCR): formultng the problem, codng n Englsh trnslton nto computer

More information

OXFORD H i g h e r E d u c a t i o n Oxford University Press, All rights reserved.

OXFORD H i g h e r E d u c a t i o n Oxford University Press, All rights reserved. Renshw: Mths for Econoics nswers to dditionl exercises Exercise.. Given: nd B 5 Find: () + B + B 7 8 (b) (c) (d) (e) B B B + B T B (where 8 B 6 B 6 8 B + B T denotes the trnspose of ) T 8 B 5 (f) (g) B

More information

GAUSS ELIMINATION. Consider the following system of algebraic linear equations

GAUSS ELIMINATION. Consider the following system of algebraic linear equations Numercl Anlyss for Engneers Germn Jordnn Unversty GAUSS ELIMINATION Consder the followng system of lgebrc lner equtons To solve the bove system usng clsscl methods, equton () s subtrcted from equton ()

More information

Least Squares Fitting of Data

Least Squares Fitting of Data Least Squares Fttng of Data Davd Eberly Geoetrc Tools, LLC http://www.geoetrctools.co/ Copyrght c 1998-2014. All Rghts Reserved. Created: July 15, 1999 Last Modfed: February 9, 2008 Contents 1 Lnear Fttng

More information

Two Coefficients of the Dyson Product

Two Coefficients of the Dyson Product Two Coeffcents of the Dyson Product rxv:07.460v mth.co 7 Nov 007 Lun Lv, Guoce Xn, nd Yue Zhou 3,,3 Center for Combntorcs, LPMC TJKLC Nnk Unversty, Tnjn 30007, P.R. Chn lvlun@cfc.nnk.edu.cn gn@nnk.edu.cn

More information

System in Weibull Distribution

System in Weibull Distribution Internatonal Matheatcal Foru 4 9 no. 9 94-95 Relablty Equvalence Factors of a Seres-Parallel Syste n Webull Dstrbuton M. A. El-Dacese Matheatcs Departent Faculty of Scence Tanta Unversty Tanta Egypt eldacese@yahoo.co

More information

Numbers Related to Bernoulli-Goss Numbers

Numbers Related to Bernoulli-Goss Numbers ursh Journl of Anlyss n Nuber heory, 4, Vol., No., -8 Avlble onlne t htt://ubs.sceub.co/tnt///4 Scence n Eucton Publshng OI:.69/tnt---4 Nubers Relte to Bernoull-Goss Nubers Mohe Oul ouh Benough * érteent

More information

Least Squares Fitting of Data

Least Squares Fitting of Data Least Squares Fttng of Data Davd Eberly Geoetrc Tools, LLC http://www.geoetrctools.co/ Copyrght c 1998-2015. All Rghts Reserved. Created: July 15, 1999 Last Modfed: January 5, 2015 Contents 1 Lnear Fttng

More information

Lecture 8: Camera Calibration

Lecture 8: Camera Calibration Lecture 8: Cer Clbrton rofessor Fe-Fe L Stnford Vson Lb Fe-Fe L 9-Oct- Wht we wll lern tody? Revew cer preters Affne cer odel (roble Set (Q4)) Cer clbrton Vnshng ponts nd lnes (roble Set (Q)) Redng: [F]

More information

Chapter 2 Introduction to Algebra. Dr. Chih-Peng Li ( 李 )

Chapter 2 Introduction to Algebra. Dr. Chih-Peng Li ( 李 ) Chpter Introducton to Algebr Dr. Chh-Peng L 李 Outlne Groups Felds Bnry Feld Arthetc Constructon of Glos Feld Bsc Propertes of Glos Feld Coputtons Usng Glos Feld Arthetc Vector Spces Groups 3 Let G be set

More information

Special Relativity and Riemannian Geometry. Department of Mathematical Sciences

Special Relativity and Riemannian Geometry. Department of Mathematical Sciences Tutoral Letter 06//018 Specal Relatvty and Reannan Geoetry APM3713 Seester Departent of Matheatcal Scences IMPORTANT INFORMATION: Ths tutoral letter contans the solutons to Assgnent 06. BAR CODE Learn

More information

The Schur-Cohn Algorithm

The Schur-Cohn Algorithm Modelng, Estmton nd Otml Flterng n Sgnl Processng Mohmed Njm Coyrght 8, ISTE Ltd. Aendx F The Schur-Cohn Algorthm In ths endx, our m s to resent the Schur-Cohn lgorthm [] whch s often used s crteron for

More information

Least squares. Václav Hlaváč. Czech Technical University in Prague

Least squares. Václav Hlaváč. Czech Technical University in Prague Lest squres Václv Hlváč Czech echncl Unversty n Prgue hlvc@fel.cvut.cz http://cmp.felk.cvut.cz/~hlvc Courtesy: Fred Pghn nd J.P. Lews, SIGGRAPH 2007 Course; Outlne 2 Lner regresson Geometry of lest-squres

More information

Review of linear algebra. Nuno Vasconcelos UCSD

Review of linear algebra. Nuno Vasconcelos UCSD Revew of lner lgebr Nuno Vsconcelos UCSD Vector spces Defnton: vector spce s set H where ddton nd sclr multplcton re defned nd stsf: ) +( + ) (+ )+ 5) λ H 2) + + H 6) 3) H, + 7) λ(λ ) (λλ ) 4) H, - + 8)

More information

Applied Mathematics Letters

Applied Mathematics Letters Appled Matheatcs Letters 2 (2) 46 5 Contents lsts avalable at ScenceDrect Appled Matheatcs Letters journal hoepage: wwwelseverco/locate/al Calculaton of coeffcents of a cardnal B-splne Gradr V Mlovanovć

More information

Discussion Introduction P212, Week 1 The Scientist s Sixth Sense. Knowing what the answer will look like before you start.

Discussion Introduction P212, Week 1 The Scientist s Sixth Sense. Knowing what the answer will look like before you start. Discussion Introduction P1, Week 1 The Scientist s Sith Sense As scientist or engineer, uch of your job will be perforing clcultions, nd using clcultions perfored by others. You ll be doing plenty of tht

More information

Definition of Tracking

Definition of Tracking Trckng Defnton of Trckng Trckng: Generte some conclusons bout the moton of the scene, objects, or the cmer, gven sequence of mges. Knowng ths moton, predct where thngs re gong to project n the net mge,

More information

1 Linear Least Squares

1 Linear Least Squares Lest Squres Pge 1 1 Liner Lest Squres I will try to be consistent in nottion, with n being the number of dt points, nd m < n being the number of prmeters in model function. We re interested in solving

More information

An Ising model on 2-D image

An Ising model on 2-D image School o Coputer Scence Approte Inerence: Loopy Bele Propgton nd vrnts Prolstc Grphcl Models 0-708 Lecture 4, ov 7, 007 Receptor A Knse C Gene G Receptor B Knse D Knse E 3 4 5 TF F 6 Gene H 7 8 Hetunndn

More information

ECONOMETRIC THEORY. MODULE IV Lecture - 16 Predictions in Linear Regression Model

ECONOMETRIC THEORY. MODULE IV Lecture - 16 Predictions in Linear Regression Model ECONOMETRIC THEORY MODULE IV Lecture - 16 Predictions in Liner Regression Model Dr. Shlbh Deprtent of Mthetics nd Sttistics Indin Institute of Technology Knpur Prediction of vlues of study vrible An iportnt

More information

Model Fitting and Robust Regression Methods

Model Fitting and Robust Regression Methods Dertment o Comuter Engneerng Unverst o Clorn t Snt Cruz Model Fttng nd Robust Regresson Methods CMPE 64: Imge Anlss nd Comuter Vson H o Fttng lnes nd ellses to mge dt Dertment o Comuter Engneerng Unverst

More information

Remember: Project Proposals are due April 11.

Remember: Project Proposals are due April 11. Bonformtcs ecture Notes Announcements Remember: Project Proposls re due Aprl. Clss 22 Aprl 4, 2002 A. Hdden Mrov Models. Defntons Emple - Consder the emple we tled bout n clss lst tme wth the cons. However,

More information

A Family of Multivariate Abel Series Distributions. of Order k

A Family of Multivariate Abel Series Distributions. of Order k Appled Mthemtcl Scences, Vol. 2, 2008, no. 45, 2239-2246 A Fmly of Multvrte Abel Seres Dstrbutons of Order k Rupk Gupt & Kshore K. Ds 2 Fculty of Scence & Technology, The Icf Unversty, Agrtl, Trpur, Ind

More information

Chapter 12 Lyes KADEM [Thermodynamics II] 2007

Chapter 12 Lyes KADEM [Thermodynamics II] 2007 Chapter 2 Lyes KDEM [Therodynacs II] 2007 Gas Mxtures In ths chapter we wll develop ethods for deternng therodynac propertes of a xture n order to apply the frst law to systes nvolvng xtures. Ths wll be

More information

The graphs of Rational Functions

The graphs of Rational Functions Lecture 4 5A: The its of Rtionl Functions s x nd s x + The grphs of Rtionl Functions The grphs of rtionl functions hve severl differences compred to power functions. One of the differences is the behvior

More information

Demand. Demand and Comparative Statics. Graphically. Marshallian Demand. ECON 370: Microeconomic Theory Summer 2004 Rice University Stanley Gilbert

Demand. Demand and Comparative Statics. Graphically. Marshallian Demand. ECON 370: Microeconomic Theory Summer 2004 Rice University Stanley Gilbert Demnd Demnd nd Comrtve Sttcs ECON 370: Mcroeconomc Theory Summer 004 Rce Unversty Stnley Glbert Usng the tools we hve develoed u to ths ont, we cn now determne demnd for n ndvdul consumer We seek demnd

More information

MA 131 Lecture Notes Calculus Sections 1.5 and 1.6 (and other material)

MA 131 Lecture Notes Calculus Sections 1.5 and 1.6 (and other material) MA Lecture Notes Clculus Sections.5 nd.6 (nd other teril) Algebr o Functions Su, Dierence, Product, nd Quotient o Functions Let nd g be two unctions with overlpping doins. Then or ll x coon to both doins,

More information

arxiv:math/ v2 [math.ho] 16 Dec 2003

arxiv:math/ v2 [math.ho] 16 Dec 2003 rxiv:mth/0312293v2 [mth.ho] 16 Dec 2003 Clssicl Lebesgue Integrtion Theorems for the Riemnn Integrl Josh Isrlowitz 244 Ridge Rd. Rutherford, NJ 07070 jbi2@njit.edu Februry 1, 2008 Abstrct In this pper,

More information

Department of Mechanical Engineering, University of Bath. Mathematics ME Problem sheet 11 Least Squares Fitting of data

Department of Mechanical Engineering, University of Bath. Mathematics ME Problem sheet 11 Least Squares Fitting of data Deprtment of Mechncl Engneerng, Unversty of Bth Mthemtcs ME10305 Prolem sheet 11 Lest Squres Fttng of dt NOTE: If you re gettng just lttle t concerned y the length of these questons, then do hve look t

More information

r = cos θ + 1. dt ) dt. (1)

r = cos θ + 1. dt ) dt. (1) MTHE 7 Proble Set 5 Solutions (A Crdioid). Let C be the closed curve in R whose polr coordintes (r, θ) stisfy () Sketch the curve C. r = cos θ +. (b) Find pretriztion t (r(t), θ(t)), t [, b], of C in polr

More information

INTERPOLATION(1) ELM1222 Numerical Analysis. ELM1222 Numerical Analysis Dr Muharrem Mercimek

INTERPOLATION(1) ELM1222 Numerical Analysis. ELM1222 Numerical Analysis Dr Muharrem Mercimek ELM Numercl Anlss Dr Muhrrem Mercmek INTEPOLATION ELM Numercl Anlss Some of the contents re dopted from Lurene V. Fusett, Appled Numercl Anlss usng MATLAB. Prentce Hll Inc., 999 ELM Numercl Anlss Dr Muhrrem

More information

Properties of Integrals, Indefinite Integrals. Goals: Definition of the Definite Integral Integral Calculations using Antiderivatives

Properties 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 information

and that at t = 0 the object is at position 5. Find the position of the object at t = 2.

and that at t = 0 the object is at position 5. Find the position of the object at t = 2. 7.2 The Fundmentl Theorem of Clculus 49 re mny, mny problems tht pper much different on the surfce but tht turn out to be the sme s these problems, in the sense tht when we try to pproimte solutions we

More information

Denote the function derivatives f(x) in given points. x a b. Using relationships (1.2), polynomials (1.1) are written in the form

Denote the function derivatives f(x) in given points. x a b. Using relationships (1.2), polynomials (1.1) are written in the form SET OF METHODS FO SOUTION THE AUHY POBEM FO STIFF SYSTEMS OF ODINAY DIFFEENTIA EUATIONS AF atypov and YuV Nulchev Insttute of Theoretcal and Appled Mechancs SB AS 639 Novosbrs ussa Introducton A constructon

More information

MATHEMATICAL MODEL AND STATISTICAL ANALYSIS OF THE TENSILE STRENGTH (Rm) OF THE STEEL QUALITY J55 API 5CT BEFORE AND AFTER THE FORMING OF THE PIPES

MATHEMATICAL MODEL AND STATISTICAL ANALYSIS OF THE TENSILE STRENGTH (Rm) OF THE STEEL QUALITY J55 API 5CT BEFORE AND AFTER THE FORMING OF THE PIPES 6 th Reserch/Exert Conference wth Interntonl Prtcton QUALITY 009, Neum, B&H, June 04 07, 009 MATHEMATICAL MODEL AND STATISTICAL ANALYSIS OF THE TENSILE STRENGTH (Rm) OF THE STEEL QUALITY J55 API 5CT BEFORE

More information

6.6 The Marquardt Algorithm

6.6 The Marquardt Algorithm 6.6 The Mqudt Algothm lmttons of the gdent nd Tylo expnson methods ecstng the Tylo expnson n tems of ch-sque devtves ecstng the gdent sech nto n tetve mtx fomlsm Mqudt's lgothm utomtclly combnes the gdent

More information

Chapter Newton-Raphson Method of Solving a Nonlinear Equation

Chapter Newton-Raphson Method of Solving a Nonlinear Equation Chpter 0.04 Newton-Rphson Method o Solvng Nonlner Equton Ater redng ths chpter, you should be ble to:. derve the Newton-Rphson method ormul,. develop the lgorthm o the Newton-Rphson method,. use the Newton-Rphson

More information

Creative Practicing. By Jimmy Wyble edited by David Oakes

Creative Practicing. By Jimmy Wyble edited by David Oakes Cretve Prctcng By Jy Wyble edted by Dvd Okes Edtors Note: Ths terl s n excert fro Jy s lecture tht he resented t Muscns Insttute on Arl, 008. Ths s the thrd eek of ten-eek qurter. In the revous eeks, he

More information

CURVE FITTING LEAST SQUARES METHOD

CURVE FITTING LEAST SQUARES METHOD Nuercl Alss for Egeers Ger Jord Uverst CURVE FITTING Although, the for of fucto represetg phscl sste s kow, the fucto tself ot be kow. Therefore, t s frequetl desred to ft curve to set of dt pots the ssued

More information

The Regulated and Riemann Integrals

The 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 information

8. INVERSE Z-TRANSFORM

8. INVERSE Z-TRANSFORM 8. INVERSE Z-TRANSFORM The proce by whch Z-trnform of tme ere, nmely X(), returned to the tme domn clled the nvere Z-trnform. The nvere Z-trnform defned by: Computer tudy Z X M-fle trn.m ued to fnd nvere

More information

Math 8 Winter 2015 Applications of Integration

Math 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 information

4.4 Areas, Integrals and Antiderivatives

4.4 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 information

Research Article On the Upper Bounds of Eigenvalues for a Class of Systems of Ordinary Differential Equations with Higher Order

Research Article On the Upper Bounds of Eigenvalues for a Class of Systems of Ordinary Differential Equations with Higher Order Hndw Publshng Corporton Interntonl Journl of Dfferentl Equtons Volume 0, Artcle ID 7703, pges do:055/0/7703 Reserch Artcle On the Upper Bounds of Egenvlues for Clss of Systems of Ordnry Dfferentl Equtons

More information

Overview of Calculus I

Overview of Calculus I Overview of Clculus I Prof. Jim Swift Northern Arizon University There re three key concepts in clculus: The limit, the derivtive, nd the integrl. You need to understnd the definitions of these three things,

More information

Variable time amplitude amplification and quantum algorithms for linear algebra. Andris Ambainis University of Latvia

Variable time amplitude amplification and quantum algorithms for linear algebra. Andris Ambainis University of Latvia Vrble tme mpltude mplfcton nd quntum lgorthms for lner lgebr Andrs Ambns Unversty of Ltv Tlk outlne. ew verson of mpltude mplfcton;. Quntum lgorthm for testng f A s sngulr; 3. Quntum lgorthm for solvng

More information

Many-Body Calculations of the Isotope Shift

Many-Body Calculations of the Isotope Shift Mny-Body Clcultons of the Isotope Shft W. R. Johnson Mrch 11, 1 1 Introducton Atomc energy levels re commonly evluted ssumng tht the nucler mss s nfnte. In ths report, we consder correctons to tomc levels

More information

8 Transportation Problem Alpha-Beta

8 Transportation Problem Alpha-Beta 8 rnsportton Proble Alph-Bet Now, we ntroduce n ddtonl lgorth for the Htchcock rnsportton proble, whch ws lredy ntroduced before hs s the Alph-Bet Algorth It copletes the lst of soluton pproches for solvng

More information

NUMERICAL MODELLING OF A CILIUM USING AN INTEGRAL EQUATION

NUMERICAL MODELLING OF A CILIUM USING AN INTEGRAL EQUATION NUEICAL ODELLING OF A CILIU USING AN INTEGAL EQUATION IHAI EBICAN, DANIEL IOAN Key words: Cl, Numercl nlyss, Electromgnetc feld, gnetton. The pper presents fst nd ccurte method to model the mgnetc behvour

More information

The Atwood Machine OBJECTIVE INTRODUCTION APPARATUS THEORY

The Atwood Machine OBJECTIVE INTRODUCTION APPARATUS THEORY The Atwood Mchine OBJECTIVE To derive the ening of Newton's second lw of otion s it pplies to the Atwood chine. To explin how ss iblnce cn led to the ccelertion of the syste. To deterine the ccelertion

More information

COMPLEX NUMBERS INDEX

COMPLEX NUMBERS INDEX COMPLEX NUMBERS INDEX. The hstory of the complex numers;. The mgnry unt I ;. The Algerc form;. The Guss plne; 5. The trgonometrc form;. The exponentl form; 7. The pplctons of the complex numers. School

More information

econstor Make Your Publication Visible

econstor Make Your Publication Visible econstor Mke Your Publcton Vsble A Servce of Wrtschft Centre zbwlebnz-infortonszentru Econocs Etukudo I. A. Artcle Optl desgns pproch to portfolo selecton CB Journl of Appled Sttstcs Provded n Cooperton

More information

ACCESS TO SCIENCE, ENGINEERING AND AGRICULTURE: MATHEMATICS 1 MATH00030 SEMESTER /2019

ACCESS TO SCIENCE, ENGINEERING AND AGRICULTURE: MATHEMATICS 1 MATH00030 SEMESTER /2019 ACCESS TO SCIENCE, ENGINEERING AND AGRICULTURE: MATHEMATICS MATH00030 SEMESTER 208/209 DR. ANTHONY BROWN 7.. Introduction to Integrtion. 7. Integrl Clculus As ws the cse with the chpter on differentil

More information

Lesson 1: Quadratic Equations

Lesson 1: Quadratic Equations Lesson 1: Qudrtic Equtions Qudrtic Eqution: The qudrtic eqution in form is. In this section, we will review 4 methods of qudrtic equtions, nd when it is most to use ech method. 1. 3.. 4. Method 1: Fctoring

More information

Lecture 36. Finite Element Methods

Lecture 36. Finite Element Methods CE 60: Numercl Methods Lecture 36 Fnte Element Methods Course Coordntor: Dr. Suresh A. Krth, Assocte Professor, Deprtment of Cvl Engneerng, IIT Guwht. In the lst clss, we dscussed on the ppromte methods

More information

,..., k N. , k 2. ,..., k i. The derivative with respect to temperature T is calculated by using the chain rule: & ( (5) dj j dt = "J j. k i.

,..., k N. , k 2. ,..., k i. The derivative with respect to temperature T is calculated by using the chain rule: & ( (5) dj j dt = J j. k i. Suppleentary Materal Dervaton of Eq. 1a. Assue j s a functon of the rate constants for the N coponent reactons: j j (k 1,,..., k,..., k N ( The dervatve wth respect to teperature T s calculated by usng

More information

Expectation and Variance

Expectation and Variance Expecttion nd Vrince : sum of two die rolls P(= P(= = 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 P(=2) = 1/36 P(=3) = 1/18 P(=4) = 1/12 P(=5) = 1/9 P(=7) = 1/6 P(=13) =? 2 1/36 3 1/18 4 1/12 5 1/9 6 5/36 7 1/6

More information

Proof that if Voting is Perfect in One Dimension, then the First. Eigenvector Extracted from the Double-Centered Transformed

Proof that if Voting is Perfect in One Dimension, then the First. Eigenvector Extracted from the Double-Centered Transformed Proof tht f Votng s Perfect n One Dmenson, then the Frst Egenvector Extrcted from the Doule-Centered Trnsformed Agreement Score Mtrx hs the Sme Rn Orderng s the True Dt Keth T Poole Unversty of Houston

More information

Math Lecture 23

Math Lecture 23 Mth 8 - Lecture 3 Dyln Zwick Fll 3 In our lst lecture we delt with solutions to the system: x = Ax where A is n n n mtrix with n distinct eigenvlues. As promised, tody we will del with the question of

More information

COMPLEX NUMBER & QUADRATIC EQUATION

COMPLEX NUMBER & QUADRATIC EQUATION MCQ COMPLEX NUMBER & QUADRATIC EQUATION Syllus : Comple numers s ordered prs of rels, Representton of comple numers n the form + nd ther representton n plne, Argnd dgrm, lger of comple numers, modulus

More information

Unit #9 : Definite Integral Properties; Fundamental Theorem of Calculus

Unit #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 information

Lecture 8: Camera Calibra0on

Lecture 8: Camera Calibra0on Lecture 8: Cer Clbron rofessor Fe- Fe L Stnford Vson Lb Lecture 8 -! Wht we wll lern tody? Revew cer preters Affne cer odel (roble Set (Q4)) Cer clbron Vnshng ponts nd lnes (roble Set (Q)) Redng: [F] Chpter

More information

Chapters 4 & 5 Integrals & Applications

Chapters 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 information

Analysis of Geometric, Zernike and United Moment Invariants Techniques Based on Intra-class Evaluation

Analysis of Geometric, Zernike and United Moment Invariants Techniques Based on Intra-class Evaluation 0 Ffth Interntonl Conference on Intellgent Systes, odellng nd Sulton Anlyss of Geoetrc, ernke nd Unted oent Invrnts Technques Bsed on Intr-clss Evluton ohd Wf srudn *, Shhrul z Ykob, Roze Rzf Othn, Iszdy

More information

n f(x i ) x. i=1 In section 4.2, we defined the definite integral of f from x = a to x = b as n f(x i ) x; f(x) dx = lim i=1

n f(x i ) x. i=1 In section 4.2, we defined the definite integral of f from x = a to x = b as n f(x i ) x; f(x) dx = lim i=1 The Fundmentl Theorem of Clculus As we continue to study the re problem, let s think bck to wht we know bout computing res of regions enclosed by curves. If we wnt to find the re of the region below the

More information

Introduction to Numerical Integration Part II

Introduction to Numerical Integration Part II Introducton to umercl Integrton Prt II CS 75/Mth 75 Brn T. Smth, UM, CS Dept. Sprng, 998 4/9/998 qud_ Intro to Gussn Qudrture s eore, the generl tretment chnges the ntegrton prolem to ndng the ntegrl w

More information

Predict Global Earth Temperature using Linier Regression

Predict Global Earth Temperature using Linier Regression Predict Globl Erth Temperture using Linier Regression Edwin Swndi Sijbt (23516012) Progrm Studi Mgister Informtik Sekolh Teknik Elektro dn Informtik ITB Jl. Gnesh 10 Bndung 40132, Indonesi 23516012@std.stei.itb.c.id

More information

LOCAL FRACTIONAL LAPLACE SERIES EXPANSION METHOD FOR DIFFUSION EQUATION ARISING IN FRACTAL HEAT TRANSFER

LOCAL FRACTIONAL LAPLACE SERIES EXPANSION METHOD FOR DIFFUSION EQUATION ARISING IN FRACTAL HEAT TRANSFER Yn, S.-P.: Locl Frctonl Lplce Seres Expnson Method for Dffuson THERMAL SCIENCE, Yer 25, Vol. 9, Suppl., pp. S3-S35 S3 LOCAL FRACTIONAL LAPLACE SERIES EXPANSION METHOD FOR DIFFUSION EQUATION ARISING IN

More information

Recitation 3: More Applications of the Derivative

Recitation 3: More Applications of the Derivative Mth 1c TA: Pdric Brtlett Recittion 3: More Applictions of the Derivtive Week 3 Cltech 2012 1 Rndom Question Question 1 A grph consists of the following: A set V of vertices. A set E of edges where ech

More information

Homework Solution - Set 5 Due: Friday 10/03/08

Homework Solution - Set 5 Due: Friday 10/03/08 CE 96 Introduction to the Theory of Computtion ll 2008 Homework olution - et 5 Due: ridy 10/0/08 1. Textook, Pge 86, Exercise 1.21. () 1 2 Add new strt stte nd finl stte. Mke originl finl stte non-finl.

More information

4. More general extremum principles and thermodynamic potentials

4. More general extremum principles and thermodynamic potentials 4. More generl etremum prncples nd thermodynmc potentls We hve seen tht mn{u(s, X )} nd m{s(u, X)} mply one nother. Under certn condtons, these prncples re very convenent. For emple, ds = 1 T du T dv +

More information

Chapter 0. What is the Lebesgue integral about?

Chapter 0. What is the Lebesgue integral about? Chpter 0. Wht is the Lebesgue integrl bout? The pln is to hve tutoril sheet ech week, most often on Fridy, (to be done during the clss) where you will try to get used to the ides introduced in the previous

More information

Before we can begin Ch. 3 on Radicals, we need to be familiar with perfect squares, cubes, etc. Try and do as many as you can without a calculator!!!

Before we can begin Ch. 3 on Radicals, we need to be familiar with perfect squares, cubes, etc. Try and do as many as you can without a calculator!!! Nme: Algebr II Honors Pre-Chpter Homework Before we cn begin Ch on Rdicls, we need to be fmilir with perfect squres, cubes, etc Try nd do s mny s you cn without clcultor!!! n The nth root of n n Be ble

More information

4 7x =250; 5 3x =500; Read section 3.3, 3.4 Announcements: Bell Ringer: Use your calculator to solve

4 7x =250; 5 3x =500; Read section 3.3, 3.4 Announcements: Bell Ringer: Use your calculator to solve Dte: 3/14/13 Objective: SWBAT pply properties of exponentil functions nd will pply properties of rithms. Bell Ringer: Use your clcultor to solve 4 7x =250; 5 3x =500; HW Requests: Properties of Log Equtions

More information

MTH 122 Fall 2008 Essex County College Division of Mathematics Handout Version 10 1 October 14, 2008

MTH 122 Fall 2008 Essex County College Division of Mathematics Handout Version 10 1 October 14, 2008 MTH 22 Fll 28 Essex County College Division of Mthemtics Hndout Version October 4, 28 Arc Length Everyone should be fmilir with the distnce formul tht ws introduced in elementry lgebr. It is bsic formul

More information

CHOVER-TYPE LAWS OF THE ITERATED LOGARITHM FOR WEIGHTED SUMS OF ρ -MIXING SEQUENCES

CHOVER-TYPE LAWS OF THE ITERATED LOGARITHM FOR WEIGHTED SUMS OF ρ -MIXING SEQUENCES CHOVER-TYPE LAWS OF THE ITERATED LOGARITHM FOR WEIGHTED SUMS OF ρ -MIXING SEQUENCES GUANG-HUI CAI Receved 24 September 2004; Revsed 3 My 2005; Accepted 3 My 2005 To derve Bum-Ktz-type result, we estblsh

More information

THE COMBINED SHEPARD ABEL GONCHAROV UNIVARIATE OPERATOR

THE COMBINED SHEPARD ABEL GONCHAROV UNIVARIATE OPERATOR REVUE D ANALYSE NUMÉRIQUE ET DE THÉORIE DE L APPROXIMATION Tome 32, N o 1, 2003, pp 11 20 THE COMBINED SHEPARD ABEL GONCHAROV UNIVARIATE OPERATOR TEODORA CĂTINAŞ Abstrct We extend the Sheprd opertor by

More information

Improper Integrals, and Differential Equations

Improper Integrals, and Differential Equations Improper Integrls, nd Differentil Equtions October 22, 204 5.3 Improper Integrls Previously, we discussed how integrls correspond to res. More specificlly, we sid tht for function f(x), the region creted

More information

MAE140 - Linear Circuits - Fall 10 Midterm, October 28

MAE140 - Linear Circuits - Fall 10 Midterm, October 28 M140 - Lnear rcuts - Fall 10 Mdterm, October 28 nstructons () Ths exam s open book. You may use whatever wrtten materals you choose, ncludng your class notes and textbook. You may use a hand calculator

More information

V E L O C I T Y a n d V E L O C I T Y P R E S S U R E I n A I R S Y S T E M S

V E L O C I T Y a n d V E L O C I T Y P R E S S U R E I n A I R S Y S T E M S V E L O C I T Y n d V E L O C I T Y R E S S U R E I n A I R S Y S T E M S A nlysis of fluid systes using ir re usully done voluetric bsis so the pressure version of the Bernoulli eqution is used. This

More information