Transport Equation. For constant ε, the force per unit fluid volume due to electric field becomes,

Size: px
Start display at page:

Download "Transport Equation. For constant ε, the force per unit fluid volume due to electric field becomes,"

Transcription

1 Trasport Eqato For ostat ε, the fore per t fld volme de to eletr feld beomes, - ρ f E N/m 3 or ρ f ψ Mometm Eq. (trodg the eletr fore term as body fore term) ρ + ρ = p + µ d t Steady state, reep flow d + ρ g f ρ ψ.1 0 = p f + µ + ρ g ρ ψ Free harge desty s gve by, f ρ = z e = F z. F s Faraday ost. C s molar o. Mass oservato: = 0 s defed as followg

2 Coveto-Dffso-Mgrato Eq. The movemet of o spees a eletrolyt solto take plae de to blk moto, dffso bease of dfferee oetrato ad mgrato der eletr potetal. Loal mass average veloty, ρ ρ = 1 = 1 = = = 1 ρ ρ...3 s the veloty vetor of the th spees w.r.t. statoary observer s the blk fld veloty w.r.t statoary observer Molar average veloty = 1 = 1 = 1 = = spees (mol/m 3 ).3 s the molar o. of the th Molar o. (mol/m 3 ) ad mass desty (kg/m 3 ) are related by,

3 = 1000 (ρ / M ) M s the molar mass (kg/kmol) of the th spees. M = 1000 ρ Mass of a mole of a sbstae s alled molar mass ( M ) kg/kmol. It has magtde as the formerly sed moleler weght. The fator 100 appears order to reole the s gve terms of mol/m 3 ot as kmol/m 3 ot mol/l. Mass frato of the th spees s the desty of th spees dvded by the desty of the mxtre W = ρ I / ρ Smlarly molar frato, x = / The flx gve by Fk s law s prely de to dffso as a reslt of molelar moto. The molar flx of the th spees wth respet to the mass average veloty,, s gve by Fk s Law as D mol/m s

4 The flx of th spees wth respet to the statoary observer s a ombato of the ovetve flx de to blk movemet ad the dffsoal flx. Coseqetly, = ρ = ρ D ρ mass bass..4 = = D molar bass..5 For dlte solto = = D molar bass.5 The frst term the RHS s flx de to blk moto. The seod term o RHS s the flx of the th spees de to dffso resltg from the oetrato gradet,. I a eletrolyt solto sbeted to eletr feld, mgrato of o wll or. The flx de to mgrato a eletr feld s proportoal to the fore atg o the partle tmes the os oetrato,.e. The fore atg o the th spees s

5 -Z F ψ N/mol where, Z F s the harge per t mole ad F s the Faraday ostat. Ths a be expressed terms of per t volme -Z F ψ N/m 3 Addg the proportoalty ostat betwee flx ad the fore -υ Z F ψ mol/m s where, -υ I s the moblty of the o ( th spees). The t of -υ I s m mol/(j s) or mol m/(n s) The flx of the th spees s gve by, = D υ Z FC ψ molarbass...6 = ρ D ρ υ Z F ρ ψ massbass..7 I eletroket problems t s better to work wth molar bass.

6 Makg se of Nerst-Este Eq. D = R T υ The molar flx eq beomes, = D ZF D RT ψ molarbass..8 The above eqatos are kow as Nerst- Plak eq. Also, F = N a e ; k N a = R; F / RT = e / k T = N a C Makg se of the above relatos, oe a wrte flx based o mber o. = N a t: 1/m s = D Z F RT D ψ...9 Defg moblty as ω I = D / (k T) = ktω Ze ω ψ..3.0

7 Boltzma Dstrbto: Boltzma dstrbto was prevosly derved by herst argmets. Use Nerst-Plak eq (.8) to derve the expresso for Boltzma dstrbto for o mber o. Near harged srfae. Cosder a srfae wth ormal dreto as x x = x D d dx Ze k T D dψ dx Assmg at eqbm. zero fld veloty ad zero flx, d z e + d x kt or d (l d x ) z e + kt dψ =0 d x dψ = 0 d x Let = ad ψ = ψ Solto of above eq. wth b.. z = e ψ exp k T

8 Coservato of o mass Materal balae over a statoary volme elemet wth eletrolyt solto, d dt =. + R 3.1 R s the prodto rate de to hemal reato gve as mol/m 3 s, mpt term.. s the et For steady state wth o hemal reato,. = Crret Desty: The flow of rret reslt from flx of dvdal flx of all o spees preset the eletrolyt solto, = F z = e Makg se of expresso for (Nmber o. bass) z..3.3 (.9)

9 e ψ = e z edz z D kt.3.4 or (molar bass) = F z F D Z F ψ z υ 3.5 For a eletrally etral solto the frst term RHS drops ot, z = 0 Ths s eqvalet to sayg that the blk moto of zero volme harge desty a ot otrbte aythg to the rret desty. Whe there s o o. gradet, egletg the seod term to gve, = F ψ z υ or, terms of odtvty (σ) of the solto = σ ψ (Ohm s law) e σ = F where, z υ = z D kt S/m S semes = Amp/volt Molar odtvty (odtvty of oe mole of sbstae oe b meter of solto) of o spees: σ λ = = F z υ S m / mol

10 Eqvalet odtvty = λ I / z Codtvty of solto σ = λ For a sgle salt eletrolyte, σ = λ+ + + λ S/m (wrte molar odtvty of Na SO 4 oe mole oe m 3 ) Coservato of Charge: Mltplyg (3.1) by z F z = F. z F + t F z R Smmg over all spees: F z = F. z + t F z R 0 0 steady state homogeeos rx whh s or eletrally etral eletrally balaed. = 0 Coservato of Charge

Module 1 : The equation of continuity. Lecture 5: Conservation of Mass for each species. & Fick s Law

Module 1 : The equation of continuity. Lecture 5: Conservation of Mass for each species. & Fick s Law Module : The equato of cotuty Lecture 5: Coservato of Mass for each speces & Fck s Law NPTEL, IIT Kharagpur, Prof. Sakat Chakraborty, Departmet of Chemcal Egeerg 2 Basc Deftos I Mass Trasfer, we usually

More information

ON A NEUMANN EQUILIBRIUM STATES IN ONE MODEL OF ECONOMIC DYNAMICS

ON A NEUMANN EQUILIBRIUM STATES IN ONE MODEL OF ECONOMIC DYNAMICS oral of re ad Appled Mathemats: Advaes ad Applatos Volme 8 Nmber 2 207 ages 87-95 Avalable at http://setfadvaes.o. DO: http://d.do.org/0.8642/pamaa_7002866 ON A NEUMANN EQULBRUM STATES N ONE MODEL OF ECONOMC

More information

u(x, t) = u 0 (x ct). This Riemann invariant u is constant along characteristics λ with x = x 0 +ct (u(x, t) = u 0 (x 0 )):

u(x, t) = u 0 (x ct). This Riemann invariant u is constant along characteristics λ with x = x 0 +ct (u(x, t) = u 0 (x 0 )): x, t, h x The Frst-Order Wave Eqato The frst-order wave advecto eqato s c > 0 t + c x = 0, x, t = 0 = 0x. The solto propagates the tal data 0 to the rght wth speed c: x, t = 0 x ct. Ths Rema varat s costat

More information

u(x, t) = u 0 (x ct). This Riemann invariant u is constant along characteristics λ with x = x 0 +ct (u(x, t) = u 0 (x 0 )):

u(x, t) = u 0 (x ct). This Riemann invariant u is constant along characteristics λ with x = x 0 +ct (u(x, t) = u 0 (x 0 )): x, t ), h x The Frst-Order Wave Eqato The frst-order wave advecto) eqato s c > 0) t + c x = 0, x, t = 0) = 0x). The solto propagates the tal data 0 to the rght wth speed c: x, t) = 0 x ct). Ths Rema varat

More information

RECIPROCAL SYMMETRY AND EQUIVALENCE BETWEEN RELATIVISTIC AND QUANTUM MECHANICAL CONCEPTS

RECIPROCAL SYMMETRY AND EQUIVALENCE BETWEEN RELATIVISTIC AND QUANTUM MECHANICAL CONCEPTS RECIPROCAL SYMMETRY AND EQUIVALENCE BETWEEN RELATIVISTIC AND QUANTUM MECHANICAL CONCEPTS Mshfq Ahmad Departmet of Physs, Rajshah Uversty, Rajshah, Bagladesh E-mal: mshfqahmad@r.a.bd ABSTRACT We have defed

More information

B-spline curves. 1. Properties of the B-spline curve. control of the curve shape as opposed to global control by using a special set of blending

B-spline curves. 1. Properties of the B-spline curve. control of the curve shape as opposed to global control by using a special set of blending B-sple crve Copyrght@, YZU Optmal Desg Laboratory. All rghts reserved. Last pdated: Yeh-Lag Hs (--9). ote: Ths s the corse materal for ME Geometrc modelg ad compter graphcs, Ya Ze Uversty. art of ths materal

More information

An Expansion of the Derivation of the Spline Smoothing Theory Alan Kaylor Cline

An Expansion of the Derivation of the Spline Smoothing Theory Alan Kaylor Cline A Epaso of the Derato of the Sple Smoothg heory Ala Kaylor Cle he classc paper "Smoothg by Sple Fctos", Nmersche Mathematk 0, 77-83 967) by Chrsta Resch showed that atral cbc sples were the soltos to a

More information

LOAD-FLOW CALCULATIONS IN MESHED SYSTEMS Node voltage method A system part with the node k and its direct neighbour m

LOAD-FLOW CALCULATIONS IN MESHED SYSTEMS Node voltage method A system part with the node k and its direct neighbour m LOAD-FLOW CALCLATIONS IN MESHED SYSTEMS Node oltage method A system part wth the ode ad ts dret eghbor m Î Îm Î m m Crrets Î m m m Î Î m m m m Î m m m m m m m Let s dee the ode sel-admttae (adm. matr dagoal

More information

ECE606: Solid State Devices Lecture 11 Interface States Recombination Carrier Transport

ECE606: Solid State Devices Lecture 11 Interface States Recombination Carrier Transport C606: Sold State eves Leture Iterfae States Reombato Carrer Trasport Gerhard Klmek geko@purdue.edu Outle ) SRH formula adapted to terfae states ) Surfae reombato depleto rego 3) Coluso Surfae Reombato

More information

Numerical Solutions to Partial Differential Equations

Numerical Solutions to Partial Differential Equations Nmeral Soltos to Partal Dfferetal Eqatos Dr. Ismal Celk Referee: Celk, I. (00 ) Itrodtory Nmeral Methods for Egeerg Aapplatos, Ararat Books & Pblshg, Morgatow WV araratbp@gmal.om; www.araratbp.freeservers.om

More information

Open and Closed Networks of M/M/m Type Queues (Jackson s Theorem for Open and Closed Networks) Copyright 2015, Sanjay K. Bose 1

Open and Closed Networks of M/M/m Type Queues (Jackson s Theorem for Open and Closed Networks) Copyright 2015, Sanjay K. Bose 1 Ope ad Closed Networks of //m Type Qees Jackso s Theorem for Ope ad Closed Networks Copyrght 05, Saay. Bose p osso Rate λp osso rocess Average Rate λ p osso Rate λp N p p N osso Rate λp N Splttg a osso

More information

STK3100 and STK4100 Autumn 2018

STK3100 and STK4100 Autumn 2018 SK3 ad SK4 Autum 8 Geeralzed lear models Part III Covers the followg materal from chaters 4 ad 5: Cofdece tervals by vertg tests Cosder a model wth a sgle arameter β We may obta a ( α% cofdece terval for

More information

DISTURBANCE TERMS. is a scalar and x i

DISTURBANCE TERMS. is a scalar and x i DISTURBANCE TERMS I a feld of research desg, we ofte have the qesto abot whether there s a relatoshp betwee a observed varable (sa, ) ad the other observed varables (sa, x ). To aswer the qesto, we ma

More information

2. Higher Order Consensus

2. Higher Order Consensus Prepared by F.L. Lews Updated: Wedesday, February 3, 0. Hgher Order Cosesus I Seto we dsussed ooperatve otrol o graphs for dyamal systems that have frstorder dyams, that s, a sgle tegrator or shft regster

More information

Third handout: On the Gini Index

Third handout: On the Gini Index Thrd hadout: O the dex Corrado, a tala statstca, proposed (, 9, 96) to measure absolute equalt va the mea dfferece whch s defed as ( / ) where refers to the total umber of dvduals socet. Assume that. The

More information

Section 2:00 ~ 2:50 pm Thursday in Maryland 202 Sep. 29, 2005

Section 2:00 ~ 2:50 pm Thursday in Maryland 202 Sep. 29, 2005 Seto 2:00 ~ 2:50 pm Thursday Marylad 202 Sep. 29, 2005. Homework assgmets set ad 2 revews: Set : P. A box otas 3 marbles, red, gree, ad blue. Cosder a expermet that ossts of takg marble from the box, the

More information

THE ACOUSTIC WAVE PROPAGATION EQUATION IN A TURBULENT COMBUSTING FLOW

THE ACOUSTIC WAVE PROPAGATION EQUATION IN A TURBULENT COMBUSTING FLOW ICSV14 Cars Australa 9-1 July, 7 THE ACOUSTIC WAVE PROPAGATION EQUATION IN A TURBULENT COMBUSTING FLOW Jm B.W. Kok ad Bram de Jager Uversty of Twete Dept. of Meh Eg. PO Box 17, 75 AE Eshede The Netherlads.b.w.kok@utwete.l

More information

Applying the condition for equilibrium to this equilibrium, we get (1) n i i =, r G and 5 i

Applying the condition for equilibrium to this equilibrium, we get (1) n i i =, r G and 5 i CHEMICAL EQUILIBRIA The Thermodyamc Equlbrum Costat Cosder a reversble reacto of the type 1 A 1 + 2 A 2 + W m A m + m+1 A m+1 + Assgg postve values to the stochometrc coeffcets o the rght had sde ad egatve

More information

{ }{ ( )} (, ) = ( ) ( ) ( ) Chapter 14 Exercises in Sampling Theory. Exercise 1 (Simple random sampling): Solution:

{ }{ ( )} (, ) = ( ) ( ) ( ) Chapter 14 Exercises in Sampling Theory. Exercise 1 (Simple random sampling): Solution: Chapter 4 Exercses Samplg Theory Exercse (Smple radom samplg: Let there be two correlated radom varables X ad A sample of sze s draw from a populato by smple radom samplg wthout replacemet The observed

More information

TESTS BASED ON MAXIMUM LIKELIHOOD

TESTS BASED ON MAXIMUM LIKELIHOOD ESE 5 Toy E. Smth. The Basc Example. TESTS BASED ON MAXIMUM LIKELIHOOD To llustrate the propertes of maxmum lkelhood estmates ad tests, we cosder the smplest possble case of estmatg the mea of the ormal

More information

Lecture 3. Sampling, sampling distributions, and parameter estimation

Lecture 3. Sampling, sampling distributions, and parameter estimation Lecture 3 Samplg, samplg dstrbutos, ad parameter estmato Samplg Defto Populato s defed as the collecto of all the possble observatos of terest. The collecto of observatos we take from the populato s called

More information

2.160 System Identification, Estimation, and Learning Lecture Notes No. 17 April 24, 2006

2.160 System Identification, Estimation, and Learning Lecture Notes No. 17 April 24, 2006 .6 System Idetfcato, Estmato, ad Learg Lectre Notes No. 7 Aprl 4, 6. Iformatve Expermets. Persstece of Exctato Iformatve data sets are closely related to Persstece of Exctato, a mportat cocept sed adaptve

More information

Functions of Random Variables

Functions of Random Variables Fuctos of Radom Varables Chapter Fve Fuctos of Radom Varables 5. Itroducto A geeral egeerg aalyss model s show Fg. 5.. The model output (respose) cotas the performaces of a system or product, such as weght,

More information

Processing of Information with Uncertain Boundaries Fuzzy Sets and Vague Sets

Processing of Information with Uncertain Boundaries Fuzzy Sets and Vague Sets Processg of Iformato wth Ucerta odares Fzzy Sets ad Vage Sets JIUCHENG XU JUNYI SHEN School of Electroc ad Iformato Egeerg X'a Jaotog Uversty X'a 70049 PRCHIN bstract: - I the paper we aalyze the relatoshps

More information

Alternating Direction Implicit Method

Alternating Direction Implicit Method Alteratg Drecto Implct Method Whle dealg wth Ellptc Eqatos the Implct form the mber of eqatos to be solved are N M whch are qte large mber. Thogh the coeffcet matrx has may zeros bt t s ot a baded system.

More information

Math 10 Discrete Mathematics

Math 10 Discrete Mathematics Math 0 Dsrete Mathemats T. Heso REVIEW EXERCISES FOR EXM II Whle these problems are represetatve of the types of problems that I mght put o a exam, they are ot lusve. You should be prepared to work ay

More information

MOLECULAR VIBRATIONS

MOLECULAR VIBRATIONS MOLECULAR VIBRATIONS Here we wsh to vestgate molecular vbratos ad draw a smlarty betwee the theory of molecular vbratos ad Hückel theory. 1. Smple Harmoc Oscllator Recall that the eergy of a oe-dmesoal

More information

Summary of the lecture in Biostatistics

Summary of the lecture in Biostatistics Summary of the lecture Bostatstcs Probablty Desty Fucto For a cotuos radom varable, a probablty desty fucto s a fucto such that: 0 dx a b) b a dx A probablty desty fucto provdes a smple descrpto of the

More information

7.0 Equality Contraints: Lagrange Multipliers

7.0 Equality Contraints: Lagrange Multipliers Systes Optzato 7.0 Equalty Cotrats: Lagrage Multplers Cosder the zato of a o-lear fucto subject to equalty costrats: g f() R ( ) 0 ( ) (7.) where the g ( ) are possbly also olear fuctos, ad < otherwse

More information

Lecture 8: Electrons and hole currents, IC Resistors. Announcements

Lecture 8: Electrons and hole currents, IC Resistors. Announcements EECS 15 Sprg 4, Leture 8 Leture 8: Eletros a hole urrets, IC Resstors EECS 15 Sprg 4, Leture 8 Aouemets The mterm s sheule for Marh 1, 6-8 pm, Sbley Autorum The thr homework s ue Weesay /11 1 EECS 15 Sprg

More information

STK3100 and STK4100 Autumn 2017

STK3100 and STK4100 Autumn 2017 SK3 ad SK4 Autum 7 Geeralzed lear models Part III Covers the followg materal from chaters 4 ad 5: Sectos 4..5, 4.3.5, 4.3.6, 4.4., 4.4., ad 4.4.3 Sectos 5.., 5.., ad 5.5. Ørulf Borga Deartmet of Mathematcs

More information

ECE 595, Section 10 Numerical Simulations Lecture 19: FEM for Electronic Transport. Prof. Peter Bermel February 22, 2013

ECE 595, Section 10 Numerical Simulations Lecture 19: FEM for Electronic Transport. Prof. Peter Bermel February 22, 2013 ECE 595, Secto 0 Numercal Smulatos Lecture 9: FEM for Electroc Trasport Prof. Peter Bermel February, 03 Outle Recap from Wedesday Physcs-based devce modelg Electroc trasport theory FEM electroc trasport

More information

ECE 6340 Intermediate EM Waves. Fall Prof. David R. Jackson Dept. of ECE. Notes 3

ECE 6340 Intermediate EM Waves. Fall Prof. David R. Jackson Dept. of ECE. Notes 3 C 634 Intermedate M Waves Fall 216 Prof. Davd R. akson Dept. of C Notes 3 1 Types of Current ρ v Note: The free-harge densty ρ v refers to those harge arrers (ether postve or negatve) that are free to

More information

The acoustic wave propagation equation in a turbulent combusting flow

The acoustic wave propagation equation in a turbulent combusting flow Aousts 8 Pars The aoust wave propagato equato a turbulet ombustg low J. B. W. Kok Uversty o Twete, P.O. Box 17, 75 AE Eshede, Netherlads.b.w.kok@utwete.l 761 Aousts 8 Pars Abstrat Soud geerato by turbulet

More information

We have already referred to a certain reaction, which takes place at high temperature after rich combustion.

We have already referred to a certain reaction, which takes place at high temperature after rich combustion. ME 41 Day 13 Topcs Chemcal Equlbrum - Theory Chemcal Equlbrum Example #1 Equlbrum Costats Chemcal Equlbrum Example #2 Chemcal Equlbrum of Hot Bured Gas 1. Chemcal Equlbrum We have already referred to a

More information

Lecture 07: Poles and Zeros

Lecture 07: Poles and Zeros Lecture 07: Poles ad Zeros Defto of poles ad zeros The trasfer fucto provdes a bass for determg mportat system respose characterstcs wthout solvg the complete dfferetal equato. As defed, the trasfer fucto

More information

X X X E[ ] E X E X. is the ()m n where the ( i,)th. j element is the mean of the ( i,)th., then

X X X E[ ] E X E X. is the ()m n where the ( i,)th. j element is the mean of the ( i,)th., then Secto 5 Vectors of Radom Varables Whe workg wth several radom varables,,..., to arrage them vector form x, t s ofte coveet We ca the make use of matrx algebra to help us orgaze ad mapulate large umbers

More information

Homework #2 Solutions, EE/MSE 486, Spring 2017 Problem 1:

Homework #2 Solutions, EE/MSE 486, Spring 2017 Problem 1: Homework # Solutos, EE/MSE 486, Sprg 017 Problem 1: P o p N N A ( N N A) Here / for type dopg; 4 p p N A N ( N A N) / for p type dog. 4 At 1000C, 3.1*10 16 3/ From the table the otes, we have T 0.603eV

More information

Carrier Action under Perturbation

Carrier Action under Perturbation Carrer Acto uder Perturbato Eulbrum: o curret ad o formato ca be represeted. Ferm-level s flat! Perturbato s ecessary to artfcally ecode formato perturbed states: electrc feld (drft), cocetrato gradet

More information

Log1 Contest Round 2 Theta Complex Numbers. 4 points each. 5 points each

Log1 Contest Round 2 Theta Complex Numbers. 4 points each. 5 points each 01 Log1 Cotest Roud Theta Complex Numbers 1 Wrte a b Wrte a b form: 1 5 form: 1 5 4 pots each Wrte a b form: 65 4 4 Evaluate: 65 5 Determe f the followg statemet s always, sometmes, or ever true (you may

More information

(This summarizes what you basically need to know about joint distributions in this course.)

(This summarizes what you basically need to know about joint distributions in this course.) HG Ot. ECON 430 H Extra exerses for o-semar week 4 (Solutos wll be put o the et at the ed of the week) Itroduto: Revew of multdmesoal dstrbutos (Ths summarzes what you basally eed to kow about jot dstrbutos

More information

Ruin Probability-Based Initial Capital of the Discrete-Time Surplus Process

Ruin Probability-Based Initial Capital of the Discrete-Time Surplus Process Ru Probablty-Based Ital Captal of the Dsrete-Tme Surplus Proess by Parote Sattayatham, Kat Sagaroo, ad Wathar Klogdee AbSTRACT Ths paper studes a surae model uder the regulato that the surae ompay has

More information

Chapter Gauss-Seidel Method

Chapter Gauss-Seidel Method Chpter 04.08 Guss-Sedel Method After redg ths hpter, you should be ble to:. solve set of equtos usg the Guss-Sedel method,. reogze the dvtges d ptflls of the Guss-Sedel method, d. determe uder wht odtos

More information

ρ < 1 be five real numbers. The

ρ < 1 be five real numbers. The Lecture o BST 63: Statstcal Theory I Ku Zhag, /0/006 Revew for the prevous lecture Deftos: covarace, correlato Examples: How to calculate covarace ad correlato Theorems: propertes of correlato ad covarace

More information

ECE606: Solid State Devices Lecture 13 Solutions of the Continuity Eqs. Analytical & Numerical

ECE606: Solid State Devices Lecture 13 Solutions of the Continuity Eqs. Analytical & Numerical ECE66: Sold State Devces Lecture 13 Solutos of the Cotuty Eqs. Aalytcal & Numercal Gerhard Klmeck gekco@purdue.edu Outle Aalytcal Solutos to the Cotuty Equatos 1) Example problems ) Summary Numercal Solutos

More information

Design maintenanceand reliability of engineering systems: a probability based approach

Design maintenanceand reliability of engineering systems: a probability based approach Desg mateaead relablty of egeerg systems: a probablty based approah CHPTER 2. BSIC SET THEORY 2.1 Bas deftos Sets are the bass o whh moder probablty theory s defed. set s a well-defed olleto of objets.

More information

Lecture 10: Condensed matter systems

Lecture 10: Condensed matter systems Lectue 0: Codesed matte systems Itoducg matte ts codesed state.! Ams: " Idstgushable patcles ad the quatum atue of matte: # Cosequeces # Revew of deal gas etopy # Femos ad Bosos " Quatum statstcs. # Occupato

More information

CHAPTER VI Statistical Analysis of Experimental Data

CHAPTER VI Statistical Analysis of Experimental Data Chapter VI Statstcal Aalyss of Expermetal Data CHAPTER VI Statstcal Aalyss of Expermetal Data Measuremets do ot lead to a uque value. Ths s a result of the multtude of errors (maly radom errors) that ca

More information

UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS

UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS Exam: ECON430 Statstcs Date of exam: Frday, December 8, 07 Grades are gve: Jauary 4, 08 Tme for exam: 0900 am 00 oo The problem set covers 5 pages Resources allowed:

More information

best estimate (mean) for X uncertainty or error in the measurement (systematic, random or statistical) best

best estimate (mean) for X uncertainty or error in the measurement (systematic, random or statistical) best Error Aalyss Preamble Wheever a measuremet s made, the result followg from that measuremet s always subject to ucertaty The ucertaty ca be reduced by makg several measuremets of the same quatty or by mprovg

More information

MA 524 Homework 6 Solutions

MA 524 Homework 6 Solutions MA 524 Homework 6 Solutos. Sce S(, s the umber of ways to partto [] to k oempty blocks, ad c(, s the umber of ways to partto to k oempty blocks ad also the arrage each block to a cycle, we must have S(,

More information

MONOPOLISTIC COMPETITION MODEL

MONOPOLISTIC COMPETITION MODEL MONOPOLISTIC COMPETITION MODEL Key gredets Cosumer utlty: log (/ ) log (taste for varety of dfferetated goods) Produto of dfferetated produts: y (/ b) max[ f, ] (reasg returs/fxed osts) Assume that good,

More information

Investigation of Partially Conditional RP Model with Response Error. Ed Stanek

Investigation of Partially Conditional RP Model with Response Error. Ed Stanek Partally Codtoal Radom Permutato Model 7- vestgato of Partally Codtoal RP Model wth Respose Error TRODUCTO Ed Staek We explore the predctor that wll result a smple radom sample wth respose error whe a

More information

828. Piecewise exact solution of nonlinear momentum conservation equation with unconditional stability for time increment

828. Piecewise exact solution of nonlinear momentum conservation equation with unconditional stability for time increment 88. Pecewse exact solto of olear mometm coservato eqato wth codtoal stablty for tme cremet Chaghwa Jag, Hyoseob Km, Sokhwa Cho 3, Jho Km 4 Korea Itellectal Property Offce, Daejeo, Korea, 3 Kookm Uversty,

More information

Analyzing Control Structures

Analyzing Control Structures Aalyzg Cotrol Strutures sequeg P, P : two fragmets of a algo. t, t : the tme they tae the tme requred to ompute P ;P s t t Θmaxt,t For loops for to m do P t: the tme requred to ompute P total tme requred

More information

Some Analytical Results of the Theory of. Equivalence Measures and Stochastic Theory of. Turbulence for Non-Isothermal Flows

Some Analytical Results of the Theory of. Equivalence Measures and Stochastic Theory of. Turbulence for Non-Isothermal Flows Advaed Stdes heoretal hyss Vol 8 o 5 - HIKAI td m-hkarom htt:ddoorg988a9 Some Aalytal eslts of the heory of qvalee Measres ad Stoha heory of rblee for No-Isothermal Flos Artr V Dmtreko Deartmet of hermal

More information

Assignment 5/MATH 247/Winter Due: Friday, February 19 in class (!) (answers will be posted right after class)

Assignment 5/MATH 247/Winter Due: Friday, February 19 in class (!) (answers will be posted right after class) Assgmet 5/MATH 7/Wter 00 Due: Frday, February 9 class (!) (aswers wll be posted rght after class) As usual, there are peces of text, before the questos [], [], themselves. Recall: For the quadratc form

More information

PGE 310: Formulation and Solution in Geosystems Engineering. Dr. Balhoff. Interpolation

PGE 310: Formulation and Solution in Geosystems Engineering. Dr. Balhoff. Interpolation PGE 30: Formulato ad Soluto Geosystems Egeerg Dr. Balhoff Iterpolato Numercal Methods wth MATLAB, Recktewald, Chapter 0 ad Numercal Methods for Egeers, Chapra ad Caale, 5 th Ed., Part Fve, Chapter 8 ad

More information

International Journal of Scientific & Engineering Research, Volume 5, Issue 9, September ISSN

International Journal of Scientific & Engineering Research, Volume 5, Issue 9, September ISSN Iteratoal Joral o Scetc & Egeerg Research, Volme 5, Isse 9, September-4 5 ISSN 9-558 Nmercal Implemetato o BD va Method o Les or Tme Depedet Nolear Brgers Eqato VjthaMkda, Ashsh Awasth Departmet o Mathematcs,

More information

CHAPTER 3 POSTERIOR DISTRIBUTIONS

CHAPTER 3 POSTERIOR DISTRIBUTIONS CHAPTER 3 POSTERIOR DISTRIBUTIONS If scece caot measure the degree of probablt volved, so much the worse for scece. The practcal ma wll stck to hs apprecatve methods utl t does, or wll accept the results

More information

Chapter 3 Sampling For Proportions and Percentages

Chapter 3 Sampling For Proportions and Percentages Chapter 3 Samplg For Proportos ad Percetages I may stuatos, the characterstc uder study o whch the observatos are collected are qualtatve ature For example, the resposes of customers may marketg surveys

More information

UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS

UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS Postpoed exam: ECON430 Statstcs Date of exam: Jauary 0, 0 Tme for exam: 09:00 a.m. :00 oo The problem set covers 5 pages Resources allowed: All wrtte ad prted

More information

F A. Review1 7/1/2014. How to prepare for exams. Chapter 10 - GASES PRESSURE IS THE FORCE ACTING ON AN OBJECT PER UNIT AREA MEASUREMENT OF PRESSURE

F A. Review1 7/1/2014. How to prepare for exams. Chapter 10 - GASES PRESSURE IS THE FORCE ACTING ON AN OBJECT PER UNIT AREA MEASUREMENT OF PRESSURE How to prepare for exams 1. Uderstad EXAMLES chapter(s). Work RACICE EXERCISES 3. Work oe problem from each class of problems at ed of chapter 4. Aswer as may questos as tme permts from text web: www.prehall.com/brow

More information

Meromorphic Solutions of Nonlinear Difference Equations

Meromorphic Solutions of Nonlinear Difference Equations Mathematcal Comptato Je 014 Volme 3 Isse PP.49-54 Meromorphc Soltos of Nolear Dfferece Eatos Xogyg L # Bh Wag College of Ecoomcs Ja Uversty Gagzho Gagdog 51063 P.R.Cha #Emal: lxogyg818@163.com Abstract

More information

The Mathematical Appendix

The Mathematical Appendix The Mathematcal Appedx Defto A: If ( Λ, Ω, where ( λ λ λ whch the probablty dstrbutos,,..., Defto A. uppose that ( Λ,,..., s a expermet type, the σ-algebra o λ λ λ are defed s deoted by ( (,,...,, σ Ω.

More information

Spring Ammar Abu-Hudrouss Islamic University Gaza

Spring Ammar Abu-Hudrouss Islamic University Gaza ١ ١ Chapter Chapter 4 Cyl Blo Cyl Blo Codes Codes Ammar Abu-Hudrouss Islam Uversty Gaza Spr 9 Slde ٢ Chael Cod Theory Cyl Blo Codes A yl ode s haraterzed as a lear blo ode B( d wth the addtoal property

More information

Space charge. Lecture 8 09/11/2011. p-n junction with gradient. p-n junction with gradient. V. p-n junction. Space charge

Space charge. Lecture 8 09/11/2011. p-n junction with gradient. p-n junction with gradient. V. p-n junction. Space charge ecture 8 09/11/011 Sace charge. - jucto Sace charge th a gradet Out of equlbrum Sace charge -tye ad -tye regos Usually N >>N A thus q N x = N A /(N +N A x = N /(N +N A A ad x = The sace charge exteds towards

More information

Generative classification models

Generative classification models CS 75 Mache Learg Lecture Geeratve classfcato models Mlos Hauskrecht mlos@cs.ptt.edu 539 Seott Square Data: D { d, d,.., d} d, Classfcato represets a dscrete class value Goal: lear f : X Y Bar classfcato

More information

COV. Violation of constant variance of ε i s but they are still independent. The error term (ε) is said to be heteroscedastic.

COV. Violation of constant variance of ε i s but they are still independent. The error term (ε) is said to be heteroscedastic. c Pogsa Porchawseskul, Faculty of Ecoomcs, Chulalogkor Uversty olato of costat varace of s but they are stll depedet. C,, he error term s sad to be heteroscedastc. c Pogsa Porchawseskul, Faculty of Ecoomcs,

More information

hp calculators HP 30S Statistics Averages and Standard Deviations Average and Standard Deviation Practice Finding Averages and Standard Deviations

hp calculators HP 30S Statistics Averages and Standard Deviations Average and Standard Deviation Practice Finding Averages and Standard Deviations HP 30S Statstcs Averages ad Stadard Devatos Average ad Stadard Devato Practce Fdg Averages ad Stadard Devatos HP 30S Statstcs Averages ad Stadard Devatos Average ad stadard devato The HP 30S provdes several

More information

Continuous Distributions

Continuous Distributions 7//3 Cotuous Dstrbutos Radom Varables of the Cotuous Type Desty Curve Percet Desty fucto, f (x) A smooth curve that ft the dstrbuto 3 4 5 6 7 8 9 Test scores Desty Curve Percet Probablty Desty Fucto, f

More information

ECONOMETRIC THEORY. MODULE VIII Lecture - 26 Heteroskedasticity

ECONOMETRIC THEORY. MODULE VIII Lecture - 26 Heteroskedasticity ECONOMETRIC THEORY MODULE VIII Lecture - 6 Heteroskedastcty Dr. Shalabh Departmet of Mathematcs ad Statstcs Ida Isttute of Techology Kapur . Breusch Paga test Ths test ca be appled whe the replcated data

More information

8.1 Hashing Algorithms

8.1 Hashing Algorithms CS787: Advaced Algorthms Scrbe: Mayak Maheshwar, Chrs Hrchs Lecturer: Shuch Chawla Topc: Hashg ad NP-Completeess Date: September 21 2007 Prevously we looked at applcatos of radomzed algorthms, ad bega

More information

n -dimensional vectors follow naturally from the one

n -dimensional vectors follow naturally from the one B. Vectors ad sets B. Vectors Ecoomsts study ecoomc pheomea by buldg hghly stylzed models. Uderstadg ad makg use of almost all such models requres a hgh comfort level wth some key mathematcal sklls. I

More information

Suggested Answers, Problem Set 4 ECON The R 2 for the unrestricted model is by definition u u u u

Suggested Answers, Problem Set 4 ECON The R 2 for the unrestricted model is by definition u u u u Da Hgerma Fall 9 Sggested Aswers, Problem Set 4 ECON 333 The F-test s defed as ( SSEr The R for the restrcted model s by defto SSE / ( k ) R ( SSE / SST ) so therefore, SSE SST ( R ) ad lkewse SSEr SST

More information

d dt d d dt dt Also recall that by Taylor series, / 2 (enables use of sin instead of cos-see p.27 of A&F) dsin

d dt d d dt dt Also recall that by Taylor series, / 2 (enables use of sin instead of cos-see p.27 of A&F) dsin Learzato of the Swg Equato We wll cover sectos.5.-.6 ad begg of Secto 3.3 these otes. 1. Sgle mache-fte bus case Cosder a sgle mache coected to a fte bus, as show Fg. 1 below. E y1 V=1./_ Fg. 1 The admttace

More information

Extreme Value Theory: An Introduction

Extreme Value Theory: An Introduction (correcto d Extreme Value Theory: A Itroducto by Laures de Haa ad Aa Ferrera Wth ths webpage the authors ted to form the readers of errors or mstakes foud the book after publcato. We also gve extesos for

More information

Periodic Table of Elements. EE105 - Spring 2007 Microelectronic Devices and Circuits. The Diamond Structure. Electronic Properties of Silicon

Periodic Table of Elements. EE105 - Spring 2007 Microelectronic Devices and Circuits. The Diamond Structure. Electronic Properties of Silicon EE105 - Srg 007 Mcroelectroc Devces ad Crcuts Perodc Table of Elemets Lecture Semcoductor Bascs Electroc Proertes of Slco Slco s Grou IV (atomc umber 14) Atom electroc structure: 1s s 6 3s 3 Crystal electroc

More information

Ordinary Least Squares Regression. Simple Regression. Algebra and Assumptions.

Ordinary Least Squares Regression. Simple Regression. Algebra and Assumptions. Ordary Least Squares egresso. Smple egresso. Algebra ad Assumptos. I ths part of the course we are gog to study a techque for aalysg the lear relatoshp betwee two varables Y ad X. We have pars of observatos

More information

CIS 800/002 The Algorithmic Foundations of Data Privacy October 13, Lecture 9. Database Update Algorithms: Multiplicative Weights

CIS 800/002 The Algorithmic Foundations of Data Privacy October 13, Lecture 9. Database Update Algorithms: Multiplicative Weights CIS 800/002 The Algorthmc Foudatos of Data Prvacy October 13, 2011 Lecturer: Aaro Roth Lecture 9 Scrbe: Aaro Roth Database Update Algorthms: Multplcatve Weghts We ll recall aga) some deftos from last tme:

More information

Chemistry 163B Introduction to Multicomponent Systems and Partial Molar Quantities

Chemistry 163B Introduction to Multicomponent Systems and Partial Molar Quantities Chemstry 163B Itroducto to Multcompoet Systems ad Partal Molar Quattes 1 the problem of partal mmolar quattes mx: 10 moles ethaol C H 5 OH (580 ml) wth 1 mole water H O (18 ml) get (580+18)=598 ml of soluto?

More information

Overview. Basic concepts of Bayesian learning. Most probable model given data Coin tosses Linear regression Logistic regression

Overview. Basic concepts of Bayesian learning. Most probable model given data Coin tosses Linear regression Logistic regression Overvew Basc cocepts of Bayesa learg Most probable model gve data Co tosses Lear regresso Logstc regresso Bayesa predctos Co tosses Lear regresso 30 Recap: regresso problems Iput to learg problem: trag

More information

Econometric Methods. Review of Estimation

Econometric Methods. Review of Estimation Ecoometrc Methods Revew of Estmato Estmatg the populato mea Radom samplg Pot ad terval estmators Lear estmators Ubased estmators Lear Ubased Estmators (LUEs) Effcecy (mmum varace) ad Best Lear Ubased Estmators

More information

Physics 114 Exam 2 Fall Name:

Physics 114 Exam 2 Fall Name: Physcs 114 Exam Fall 015 Name: For gradg purposes (do ot wrte here): Questo 1. 1... 3. 3. Problem Aswer each of the followg questos. Pots for each questo are dcated red. Uless otherwse dcated, the amout

More information

Simple Linear Regression

Simple Linear Regression Statstcal Methods I (EST 75) Page 139 Smple Lear Regresso Smple regresso applcatos are used to ft a model descrbg a lear relatoshp betwee two varables. The aspects of least squares regresso ad correlato

More information

PHYS Look over. examples 2, 3, 4, 6, 7, 8,9, 10 and 11. How To Make Physics Pay PHYS Look over. Examples: 1, 4, 5, 6, 7, 8, 9, 10,

PHYS Look over. examples 2, 3, 4, 6, 7, 8,9, 10 and 11. How To Make Physics Pay PHYS Look over. Examples: 1, 4, 5, 6, 7, 8, 9, 10, PHYS Look over Chapter 9 Sectos - Eamples:, 4, 5, 6, 7, 8, 9, 0, PHYS Look over Chapter 7 Sectos -8 8, 0 eamples, 3, 4, 6, 7, 8,9, 0 ad How To ake Phscs Pa We wll ow look at a wa of calculatg where the

More information

Geometric Analogy and Products of Vectors in n Dimensions

Geometric Analogy and Products of Vectors in n Dimensions Adaces Lear Algebra & Matrx Theory 0-6 http://dxdoorg/06/alamt000 Pblshed Ole March 0 (http://wwwscrporg/oral/alamt) Geometrc Aalogy ad Prodcts of Vectors Dmesos Leoardo Smal Morera UFOA Cetro Uerstáro

More information

EVALUATION OF FUNCTIONAL INTEGRALS BY MEANS OF A SERIES AND THE METHOD OF BOREL TRANSFORM

EVALUATION OF FUNCTIONAL INTEGRALS BY MEANS OF A SERIES AND THE METHOD OF BOREL TRANSFORM EVALUATION OF FUNCTIONAL INTEGRALS BY MEANS OF A SERIES AND THE METHOD OF BOREL TRANSFORM Jose Javer Garca Moreta Ph. D research studet at the UPV/EHU (Uversty of Basque coutry) Departmet of Theoretcal

More information

CHAPTER 4 RADICAL EXPRESSIONS

CHAPTER 4 RADICAL EXPRESSIONS 6 CHAPTER RADICAL EXPRESSIONS. The th Root of a Real Number A real umber a s called the th root of a real umber b f Thus, for example: s a square root of sce. s also a square root of sce ( ). s a cube

More information

Lecture 2 - What are component and system reliability and how it can be improved?

Lecture 2 - What are component and system reliability and how it can be improved? Lecture 2 - What are compoet ad system relablty ad how t ca be mproved? Relablty s a measure of the qualty of the product over the log ru. The cocept of relablty s a exteded tme perod over whch the expected

More information

Investigating Cellular Automata

Investigating Cellular Automata Researcher: Taylor Dupuy Advsor: Aaro Wootto Semester: Fall 4 Ivestgatg Cellular Automata A Overvew of Cellular Automata: Cellular Automata are smple computer programs that geerate rows of black ad whte

More information

Non-commutative Solitons and Integrable Equations

Non-commutative Solitons and Integrable Equations Relatvty Sear at Oord No-cotatve Soltos ad Itegrable Eqatos Masash HAMANAKA Toyo U. preset Nagoya U. ro eb. MH ``Cotg lows ad Coservato aws or NC a Herarches [hep-th/6 c. MH``Nocotatve Soltos ad D-braes

More information

THE ROYAL STATISTICAL SOCIETY GRADUATE DIPLOMA

THE ROYAL STATISTICAL SOCIETY GRADUATE DIPLOMA THE ROYAL STATISTICAL SOCIETY 3 EXAMINATIONS SOLUTIONS GRADUATE DIPLOMA PAPER I STATISTICAL THEORY & METHODS The Socety provdes these solutos to assst caddates preparg for the examatos future years ad

More information

Mu Sequences/Series Solutions National Convention 2014

Mu Sequences/Series Solutions National Convention 2014 Mu Sequeces/Seres Solutos Natoal Coveto 04 C 6 E A 6C A 6 B B 7 A D 7 D C 7 A B 8 A B 8 A C 8 E 4 B 9 B 4 E 9 B 4 C 9 E C 0 A A 0 D B 0 C C Usg basc propertes of arthmetc sequeces, we fd a ad bm m We eed

More information

STATISTICS 13. Lecture 5 Apr 7, 2010

STATISTICS 13. Lecture 5 Apr 7, 2010 STATISTICS 13 Leture 5 Apr 7, 010 Revew Shape of the data -Bell shaped -Skewed -Bmodal Measures of eter Arthmet Mea Meda Mode Effets of outlers ad skewess Measures of Varablt A quattatve measure that desrbes

More information

Chemistry 163B Introduction to Multicomponent Systems and Partial Molar Quantities

Chemistry 163B Introduction to Multicomponent Systems and Partial Molar Quantities Chemstry 163 Itroducto to Multcompoet Systems ad Partal Molar Quattes 1 the problem of partal mmolar quattes mx: 10 moles ethaol C H 5 OH (580 ml) wth 1 mole water H O (18 ml) get (580+18)=598 ml of soluto?

More information

GENERALIZATIONS OF CEVA S THEOREM AND APPLICATIONS

GENERALIZATIONS OF CEVA S THEOREM AND APPLICATIONS GENERLIZTIONS OF CEV S THEOREM ND PPLICTIONS Floret Smaradache Uversty of New Mexco 200 College Road Gallup, NM 87301, US E-mal: smarad@um.edu I these paragraphs oe presets three geeralzatos of the famous

More information

K-NACCI SEQUENCES IN MILLER S GENERALIZATION OF POLYHEDRAL GROUPS * for n

K-NACCI SEQUENCES IN MILLER S GENERALIZATION OF POLYHEDRAL GROUPS * for n Iraa Joral of See & Teholog Trasato A Vol No A Prted the Islam Rebl of Ira Shraz Uverst K-NACCI SEQUENCES IN MILLER S ENERALIZATION OF POLYHEDRAL ROUPS * O DEVECI ** AND E KARADUMAN Deartmet of Mathemats

More information

Fundamentals of Regression Analysis

Fundamentals of Regression Analysis Fdametals of Regresso Aalyss Regresso aalyss s cocered wth the stdy of the depedece of oe varable, the depedet varable, o oe or more other varables, the explaatory varables, wth a vew of estmatg ad/or

More information

Chapter 1 Counting Methods

Chapter 1 Counting Methods AlbertLudwgs Uversty Freburg Isttute of Empral Researh ad Eoometrs Dr. Sevtap Kestel Mathematal Statsts - Wter 2008 Chapter Coutg Methods Am s to determe how may dfferet possbltes there are a gve stuato.

More information