Math 210 Exam 4 - Practice Problem Solutions. 1. Answer the following questions based on the rooted tree shown below:

Size: px
Start display at page:

Download "Math 210 Exam 4 - Practice Problem Solutions. 1. Answer the following questions based on the rooted tree shown below:"

Transcription

1 Mt 0 Exm 4 - Prctce Proem Soutons. Answer te foowng questons se on te roote tree sown eow: c m n o p q r s t () Lst te cren of vertex. n,o,p () Lst te ncestors of vertex s m,,,, (c) Lst te sngs of vertex q r,s,t () Fn te numer of eves n ts roote tree = (e) Lst eve vertces n ts roote tree.,,,, (f) Fn te est m for wc ts tree s roote m-ry tree. m = 4 snce m s 4 cren n no oter vertex s more tn 4 cren. (g) Fn te egt of ts roote tree. = 5. () Fn te orer tt you wou vst te vertces of ts tree f you use postorer trvers to vst te vertces.,q,r,s,t,m,,,e,,n,o,p,,f,,,g,c, () Fn te orer tt you wou vst te vertces of ts tree f you use preorer trvers to vst te vertces.,,,,,m,q,r,s,t,e,c,f,,n,o,p,g,, () Fn te orer tt you wou vst te vertces of ts tree f you use norer trvers to vst te vertces.,,q,m,r,s,t,,,e,,n,,o,p,f,c,,g,. A cn etter strts wen person sens etter to 5 peope. Ec person wo sens te etter to 5 oter peope wo ve never receve t or oes not sen t to nyone. Suppose tt 0,000 peope sen out te etter efore te cn ens n tt no one receves more tn one etter. How mny peope receve te etter? How mny peope o not sen t out? Notce tt snce every person wo sens out te etter sens t to excty 5 oter peope, n no two peope receve te etter twce, ts stuton cn e moee usng fu roote 5-ry tree. Te root represents te person wo frst sens out te etter, n te cren of ny vertex represent te 5 peope tt te rete person sent etters. From ts, we see tt = 0,000. Te tot numer of peope wo receve te etter cn e foun y computng te numer tot numer of vertces n te roote tree. Usng Teorem 4, ts s n = m+ = 5(0,000)+ = 50,00. Ts counts te root, wo strte te etter ut not receve t, so 50,000 peope receve te etter. Notce tt eves represent peope wo not m te etter to 5 oter peope. Tus, gn usng Teorem 4, = (m )+ = 4(0,000)+ = 40,00, so 40,00 peope not sen t out fter tey receve t.

2 . Prove tt every tree on n vertces s n eges. We w procee y nucton on te numer of vertces n te grp. Bse Cse: Conser tree wt n = vertces. Notce tt suc tree must ve no eges, snce tree s smpe grp n ence s no oop eges. Ten te teorem s true wen n =. Inuctve Step: Suppose tt tree wt vertces s eges. Conser tree T wt + vertces. We cm tt tere must e t est one ege n T tt s pennt ege. To see ts, conser mxm pt n T. Snce tree s no crcuts n te grp T s fnte, te fn ege n ts pt must e pennt ege. Let v e te fn vertex n te egree sequence of ts pt. Let u e te unque vertex cent to v. If we remove remove vertex v ong wt te pennt ege {u,v}, we otn grp T. We cm ts T s tree. Notce tt snce te ony ege we remove ws pennt ege, n we so remove te vertex v, ten T s connecte. Aso note tt snce eges were remove n no eges new were e, tere re no smpe crcuts n T. Ten T s tree wt vertces. Hence, ppyng te nucton ypotess to T, ts tree must ve eges. But ten te orgn tree T s eges. Ts proves te teorem.. 4. Prove tt n m-ry tree of egt s t most m eves. We w procee usng strong nucton on te egt of te tree. Bse Cse: Suppose T s roote m-ry tree wt egt. Ten T conssts of root vertex n cren of tt root vertex. Snce T s m-ry, te root s t most m cren, so te grp s t most m eves. Inuctve Step: Suppose tt ny roote m-ry tree of egt < s t most m eves. Conser n m-ry tree of egt. As ove, te root vertes of T s t most m cren. Let T,T,...,T e te sutrees of T roote t te eve cren of te root vertex. Ten m, n ec T, m cn e tougt of s roote tree wt egt t most. Usng te nuctve ypotess on ec T, ec of tese sutrees s t most m eves. However, ec ef of T s ef of one of tese sutrees, so L, te numer of eves of T stsfes te nequty L m m m = m. Ts proves te teorem.. 5. () Drw nry serc tree for te sentence Now s te tme for goo men to come to te of ter country. now s te for men goo of tme to ter come country () How mny comprsons re neee to octe te wor tme n ts tree? (c) How mny comprsons re neee to te wor wffe to ts tree? 4 6. How mny wegngs re neee to fn counterfet cons mong 8 tot cons f te counterfet cou e eter ever or gter tn norm con. Gve n gortm tt proves your nswer. Te counterfet con cn e foun n tree wegngs. Frst, use te sce to compre cons n on one se gnst cons n 4 on te oter se. Tere re two cses: Cse : Suppose te two ses o not nce. Ten te counterfet must e one of tese four cons, n te remnng four re genune. Terefore, to fn te counterfet, we weg cons n on one se gnst cons 5 n 6 on te oter se.

3 Sucse : If cons n n cons 5 n 6 nce, ten te counterfet s eter or 4. To fns, we weg con gnst con 5 (wc we now s genune). If n 5 weg te sme, ten te counterfet s con 4. Oterwse, must e te counterfet. Sucse : If cons n n cons 5 n 6 o not nce, ten te counterfet s eter or. To fns, we weg con gnst con 5 (wc we now s genune). If n 5 weg te sme, ten te counterfet s con. Oterwse, must e te counterfet. Cse : Suppose te two ses o nce. Ten te counterfet must e one of te oter four cons, n te frst four re genune. Terefore, to fn te counterfet, we weg cons n on one se gnst cons 5 n 6 on te oter se. Sucse : If cons n n cons 5 n 6 nce, ten te counterfet s eter or 8. To fns, we weg con (wc we now s genune) gnst con. If n weg te sme, ten te counterfet s con 8. Oterwse, must e te counterfet. Sucse : If cons n n cons 5 n 6 o not nce, ten te counterfet s eter 5 or 6. To fns, we weg con (wc we now s genune) gnst con 5. If n 5 weg te sme, ten te counterfet s con 6. Oterwse, 5 must e te counterfet.. How mny wegngs re neee to fn two counterfet cons mong 5 tot cons, one ever tn norm con n te oter gter tn norm con. Gve n gortm tt proves your nswer. Note tt t s posse (tougt not necessry) tt te evy n gt con to comne to weg te sme s norm cons. *** I te gortm n ecson tree for ts ter f I ve tme *** 8. Conser te foowng tree: c m n o p q () Lst te vertces n te orer tt you wou vst tem f you trverse te tree n preorer.,,,e,,,n,o,f,c,g,,,m,p,q, () Lst te vertces n te orer tt you wou vst tem f you trverse te tree n norer.,,,e,n,,o,f,,g,c,,,p,m,q, (c) Lst te vertces n te orer tt you wou vst tem f you trverse te tree n postorer.,,n,o,,e,f,,g,,p,q,m,,,c,. Conser te expresson: ( 4 ) (5+(5 ) ) () Drw te roote tree representng ts computton.

4 _ + _ 5 * _ 4 5 () Wrte ts expresson n prefx notton (c) Wrte ts expresson n postfx notton Drw posse spnnng trees for te foowng grp:

5 [I tn tt ts s compete st f you see one I msse, et me now. Te frst person to pont out ec mssng spnnng treee gets n extr cret pont]

6 . Gven te foowng grp: () Use ept frst serc to fn spnnng tree for ts grp strtng t root vertex. e c g f () Use ret frst serc to fn spnnng tree for ts grp strtng t root vertex e e c f g. For te wegte grps gven eow: 8 0 c c e f 5 g e f 5 g () Use Prm s Agortm to fn mnmum spnnng tree for ec grp. 8 0 c c 5 0 e f 5 g 4 e f 5 g 4 4 For, te eges re e n te foowng orer: {f,g},{e,f},{e,},{,},{,},{,f},{,},{,c},{c,},{g,},{,} For, te eges re e n te foowng orer: {,g},{f,g},{,},{e,},{e,},{,},{g,},{,c},{c,},{c,},{,}

7 () Use Krus s Agortm to fn mnmum spnnng tree for ec grp. 8 0 c c 5 0 e f 5 g 4 e f 5 g 4 4 For, te eges re e n te foowng orer: {f,g},{c,},{e,f},{e,},{,},{,},{g,},{,f},{,c},{g,},{,} For, te eges re e n te foowng orer: {,g},{c,},{,e},{f,g},{c,},{e,f},{e,},{,},{g,},{,c},{,}. Descre n gortm to etermne weter or not smpe connecte grp s Hmton Crcut usng ept frst serces. Strt y puttng tot orer on te vertces of te smpe connecte grp ; {v,v,...,v n }. Next, egn crryng out ept frst serc for spnnng tree strtng t v. Wenever you ve coce of wc vertex to next, coose te vertex tt ppers erest on te orere st of vertces we cose ove. Wen you cn no onger ny more vertces to your nt pt, f you ve vste every vertex, cec to see f you cn return to v usng n ege tt s not rey een use. If you cn, te pt you foun s Hmton Pt, n te ege tng you c to v cn e e to te pt to form Hmton Crcut. Oterwse, f tere s vertex tt s not yet een vste or f te en vertex s not cent to v v n unuse ege, ten te current pt cnnot e extene to Hmton Crcut. Next, go c n crry out new ept frst serc strtng t v gn, ut te frst tme you ve coce etween more tn one vertex to to te pt, coose te erest vertex t tt step not cosen n prevous pont n te constructon. Repet unt you eter construct Hmton Crcut or unt posse wys of crryng out ept frst serc ve een exuste. Note: we cn e certn tt ts gortm w prouce Hmton Crcut wenever one exsts, snce f s Hmton Crcut, f we eete one of te eges n te crcut tt re cent to v, te resut s pt grp spnnng tree of egnnng t v.

CS 541 Algorithms and Programs. Exam 1 Solutions

CS 541 Algorithms and Programs. Exam 1 Solutions CS 5 Algortms and Programs Exam Solutons Jonatan Turner 9/5/0 Be neat and concse, ut complete.. (5 ponts) An ncomplete nstance of te wgrap data structure s sown elow. Fll n te mssng felds for te adjacency

More information

A set of data can be one of three things: a normal distribution, skewed to the right or skewed to the left.

A set of data can be one of three things: a normal distribution, skewed to the right or skewed to the left. Skewness of Dt A set of t n e one of tree tings: norml istriution, skewe to te rigt or skewe to te left. norml istriution skewe to te rigt skewe to te left left sie = rigt sie mein = men ell spe rigt sie

More information

Parallel Prefix addition

Parallel Prefix addition Marcelo Kryger Sudent ID 015629850 Parallel Prefx addton The parallel prefx adder presented next, performs the addton of two bnary numbers n tme of complexty O(log n) and lnear cost O(n). Lets notce the

More information

Jonathan Turner Exam 2-12/17/03

Jonathan Turner Exam 2-12/17/03 CS 54 Aotms n Poms Fn Pom Exm St Soutons 2 Soutons Jontn Tun Exm 2-2/7/3 /28/3. (5 onts) Sow tt t y mto fo t mnmum snnn t mntns t oo nvnt un n ton of t u u. Coo nvnt. T xsts mnmum snnn t T tt nus t u s

More information

AVL Trees. Height of an AVL Tree. AVL Tree. Balancing Factor

AVL Trees. Height of an AVL Tree. AVL Tree. Balancing Factor AVL Trees AVL Tree Heigt of n AVL Tree Insertion nd restruturing Removl nd restruturing Costs AVL trees re lned. An AVL Tree is inr ser tree su tt for ever internl node v of T, te eigts of te ildren of

More information

ME 310 Numerical Methods. Differentiation

ME 310 Numerical Methods. Differentiation M 0 Numercal Metods fferentaton Tese presentatons are prepared by r. Cuneyt Sert Mecancal ngneerng epartment Mddle ast Tecncal Unversty Ankara, Turkey csert@metu.edu.tr Tey can not be used wtout te permsson

More information

Introduction to Algorithms / Algorithms I Lecturer: Michael Dinitz Topic: Splay Trees Date: 9/27/16

Introduction to Algorithms / Algorithms I Lecturer: Michael Dinitz Topic: Splay Trees Date: 9/27/16 600.463 Introduction to lgoritms / lgoritms I Lecturer: Micael initz Topic: Splay Trees ate: 9/27/16 8.1 Introduction Today we re going to talk even more about binary searc trees. -trees, red-black trees,

More information

ECON 200 EXERCISES (1,1) (d) Use your answer to show that (b) is not the equilibrium price vector if. that must be satisfied?

ECON 200 EXERCISES (1,1) (d) Use your answer to show that (b) is not the equilibrium price vector if. that must be satisfied? ECON 00 EXERCISES 4 EXCHNGE ECONOMY 4 Equilibrium in an ecange economy Tere are two consumers and wit te same utility function U ( ) ln H {, } Te aggregate endowment is tat prices sum to Tat is ( p, p)

More information

Number of Municipalities. Funding (Millions) $ April 2003 to July 2003

Number of Municipalities. Funding (Millions) $ April 2003 to July 2003 Introduction Te Department of Municipal and Provincial Affairs is responsible for matters relating to local government, municipal financing, urban and rural planning, development and engineering, and coordination

More information

A ppendix to. I soquants. Producing at Least Cost. Chapter

A ppendix to. I soquants. Producing at Least Cost. Chapter A ppendix to Chpter 0 Producing t est Cost This ppendix descries set of useful tools for studying firm s long-run production nd costs. The tools re isoqunts nd isocost lines. I soqunts FIGURE A0. SHOWS

More information

Supplementary Material for Borrowing Information across Populations in Estimating Positive and Negative Predictive Values

Supplementary Material for Borrowing Information across Populations in Estimating Positive and Negative Predictive Values Supplementary Materal for Borrong Informaton across Populatons n Estmatng Postve and Negatve Predctve Values Yng Huang, Youy Fong, Jon We $, and Zdng Feng Fred Hutcnson Cancer Researc Center, Vaccne &

More information

Lecture 5: Introduction to Entropy Coding. Thinh Nguyen Oregon State University

Lecture 5: Introduction to Entropy Coding. Thinh Nguyen Oregon State University Lecture 5: Introducton to Entropy Codng Thnh guyen Oregon State Unversty Codes Defntons: Aphabet: s a coecton of symbos. Letters (symbos): s an eement of an aphabet. Codng: the assgnment of bnary sequences

More information

2. Equlibrium and Efficiency

2. Equlibrium and Efficiency . Equlbrum and Effcency . Introducton competton and effcency Smt s nvsble and model of compettve economy combne ndependent decson-makng of consumers and frms nto a complete model of te economy exstence

More information

SUPPLEMENT TO BOOTSTRAPPING REALIZED VOLATILITY (Econometrica, Vol. 77, No. 1, January, 2009, )

SUPPLEMENT TO BOOTSTRAPPING REALIZED VOLATILITY (Econometrica, Vol. 77, No. 1, January, 2009, ) Econometrca Supplementary Materal SUPPLEMENT TO BOOTSTRAPPING REALIZED VOLATILITY Econometrca, Vol. 77, No. 1, January, 009, 83 306 BY SÍLVIA GONÇALVES AND NOUR MEDDAHI THIS SUPPLEMENT IS ORGANIZED asfollows.frst,wentroducesomenotaton.

More information

Homework 9: due Monday, 27 October, 2008

Homework 9: due Monday, 27 October, 2008 PROBLEM ONE Homework 9: due Monday, 7 October, 008. (Exercses from the book, 6 th edton, 6.6, -3.) Determne the number of dstnct orderngs of the letters gven: (a) GUIDE (b) SCHOOL (c) SALESPERSONS. (Exercses

More information

Sample Survey Design

Sample Survey Design Sample Survey Desg A Hypotetcal Exposure Scearo () Assume we kow te parameters of a worker s exposure dstrbuto of 8-our TWAs to a cemcal. As t appes, te worker as four dfferet types of days wt regard to

More information

Production and Supply Chain Management Logistics. Paolo Detti Department of Information Engeneering and Mathematical Sciences University of Siena

Production and Supply Chain Management Logistics. Paolo Detti Department of Information Engeneering and Mathematical Sciences University of Siena Producton and Supply Chan Management Logstcs Paolo Dett Department of Informaton Engeneerng and Mathematcal Scences Unversty of Sena Convergence and complexty of the algorthm Convergence of the algorthm

More information

On the uniqueness of stable marriage matchings

On the uniqueness of stable marriage matchings Economcs Letters 69 (2000) 1 8 www.elsever.com/ locate/ econbase On te unqueness of stable marrage matcngs Jan Eeckout* Unversty of Pennsylvana, Dept. of Economcs, 3718 Locust Walk, Pladelpa, PA 19104-6297,

More information

Elton, Gruber, Brown, and Goetzmann. Modern Portfolio Theory and Investment Analysis, 7th Edition. Solutions to Text Problems: Chapter 14

Elton, Gruber, Brown, and Goetzmann. Modern Portfolio Theory and Investment Analysis, 7th Edition. Solutions to Text Problems: Chapter 14 Elton, Gruer, Brown, nd Goetznn odern Portfolo Theory nd Investent Anlyss, 7th Edton Solutons to Text Proles: hpter 14 hpter 14: Prole 1 Gven the zero-et securty rket lne n ths prole, the return on the

More information

2.11 School Board Executive Compensation Practices. Introduction

2.11 School Board Executive Compensation Practices. Introduction Introduction Figure 1 As part of Education Reform in 1996-97, 27 denominational scool boards were consolidated into 10 scool boards and a Frenc-language scool board. From 1 January 1997 to 31 August 2004

More information

Understanding Annuities. Some Algebraic Terminology.

Understanding Annuities. Some Algebraic Terminology. Understandng Annutes Ma 162 Sprng 2010 Ma 162 Sprng 2010 March 22, 2010 Some Algebrac Termnology We recall some terms and calculatons from elementary algebra A fnte sequence of numbers s a functon of natural

More information

PRICE INDEX AGGREGATION: PLUTOCRATIC WEIGHTS, DEMOCRATIC WEIGHTS, AND VALUE JUDGMENTS

PRICE INDEX AGGREGATION: PLUTOCRATIC WEIGHTS, DEMOCRATIC WEIGHTS, AND VALUE JUDGMENTS Revised June 10, 2003 PRICE INDEX AGGREGATION: PLUTOCRATIC WEIGHTS, DEMOCRATIC WEIGHTS, AND VALUE JUDGMENTS Franklin M. Fiser Jane Berkowitz Carlton and Dennis William Carlton Professor of Economics Massacusetts

More information

Mathematical Modeling of Financial Derivative Pricing

Mathematical Modeling of Financial Derivative Pricing Unversty of Connectcut DgtalCommons@UConn Honors Scolar Teses Honors Scolar Program Sprng 5--207 Matematcal Modelng of Fnancal Dervatve Prcng Kelly L. Cosgrove Unversty of Connectcut, cosgrove.kelly@gmal.com

More information

A Correction to: The Structure of General Equilibrium Shadow Pricing Rules for a Tax-Distorted Economy

A Correction to: The Structure of General Equilibrium Shadow Pricing Rules for a Tax-Distorted Economy A Correcton to: Te Structure of General Equlbrum Sadow Prcng Rules for a Tax-Dstorted Economy Crs Jones Department of Economcs Faculty of Economcs and Commerce Te Australan Natonal Unversty Worng Paper

More information

Practice Exam 1. Use the limit laws from class compute the following limit. Show all your work and cite all rules used explicitly. xf(x) + 5x.

Practice Exam 1. Use the limit laws from class compute the following limit. Show all your work and cite all rules used explicitly. xf(x) + 5x. Practice Exam 1 Tese problems are meant to approximate wat Exam 1 will be like. You can expect tat problems on te exam will be of similar difficulty. Te actual exam will ave problems from sections 11.1

More information

3.1 THE 2 2 EXCHANGE ECONOMY

3.1 THE 2 2 EXCHANGE ECONOMY Essential Microeconomics -1-3.1 THE 2 2 EXCHANGE ECONOMY Private goods economy 2 Pareto efficient allocations 3 Edgewort box analysis 6 Market clearing prices and Walras Law 14 Walrasian Equilibrium 16

More information

Delocation and Trade Agreements in Imperfectly Competitive Markets (Preliminary)

Delocation and Trade Agreements in Imperfectly Competitive Markets (Preliminary) Delocation and Trade Agreements in Imperfectly Competitive Markets (Preliminary) Kyle Bagwell Stanford and NBER Robert W. Staiger Stanford and NBER June 20, 2009 Abstract We consider te purpose and design

More information

Supplemantary material to: Leverage causes fat tails and clustered volatility

Supplemantary material to: Leverage causes fat tails and clustered volatility Supplemantary material to: Leverage causes fat tails and clustered volatility Stefan Turner a,b J. Doyne Farmer b,c Jon Geanakoplos d,b a Complex Systems Researc Group, Medical University of Vienna, Wäringer

More information

EXAMINATIONS OF THE HONG KONG STATISTICAL SOCIETY

EXAMINATIONS OF THE HONG KONG STATISTICAL SOCIETY EXAMINATIONS OF THE HONG KONG STATISTICAL SOCIETY HIGHER CERTIFICATE IN STATISTICS, 2012 MODULE 8 : Survey sampling and estimation Time allowed: One and a alf ours Candidates sould answer THREE questions.

More information

What is Monte Carlo Simulation? Monte Carlo Simulation

What is Monte Carlo Simulation? Monte Carlo Simulation Wht is Monte Crlo Simultion? Monte Crlo methods re widely used clss of computtionl lgorithms for simulting the ehvior of vrious physicl nd mthemticl systems, nd for other computtions. Monte Crlo lgorithm

More information

11.1 Average Rate of Change

11.1 Average Rate of Change 11.1 Average Rate of Cange Question 1: How do you calculate te average rate of cange from a table? Question : How do you calculate te average rate of cange from a function? In tis section, we ll examine

More information

Online Appendix to Product and Pricing Decisions in Crowdfunding

Online Appendix to Product and Pricing Decisions in Crowdfunding 1 Onine Appendix to Product and Pricing Decisions in Crowdfunding A. Simutaneous versus Sequentia Modes Sequentia mecanism assumes tat two buyers arrive at te proposed project at different periods and

More information

PROPOSAL FOR RULES CHANGE

PROPOSAL FOR RULES CHANGE PROPOSAL FOR RULES CHANGE S/NO.315 Rule Cnge Title: Mrket Rules Modifiction for LNG Vesting Sceme Submitted By : Compny: Dte: Telepone No. Ms Nerine Teo Energy Mrket Compny Pte Ltd 25 September 2012 67793000

More information

Elton, Gruber, Brown, and Goetzmann. Modern Portfolio Theory and Investment Analysis, 7th Edition. Solutions to Text Problems: Chapter 16

Elton, Gruber, Brown, and Goetzmann. Modern Portfolio Theory and Investment Analysis, 7th Edition. Solutions to Text Problems: Chapter 16 lton, Gruer, rown, and Goetzmann Modern Portfolo Theory and Investment nalyss, 7th dton Solutons to Text Prolems: hapter 6 hapter 6: Prolem From the text we know that three ponts determne a plane. The

More information

ACC 471 Practice Problem Set # 4 Fall Suggested Solutions

ACC 471 Practice Problem Set # 4 Fall Suggested Solutions ACC 471 Practice Problem Set # 4 Fall 2002 Suggested Solutions 1. Text Problems: 17-3 a. From put-call parity, C P S 0 X 1 r T f 4 50 50 1 10 1 4 $5 18. b. Sell a straddle, i.e. sell a call and a put to

More information

Outline. CSE 326: Data Structures. Priority Queues Leftist Heaps & Skew Heaps. Announcements. New Heap Operation: Merge

Outline. CSE 326: Data Structures. Priority Queues Leftist Heaps & Skew Heaps. Announcements. New Heap Operation: Merge CSE 26: Dt Structures Priority Queues Leftist Heps & Skew Heps Outline Announcements Leftist Heps & Skew Heps Reding: Weiss, Ch. 6 Hl Perkins Spring 2 Lectures 6 & 4//2 4//2 2 Announcements Written HW

More information

Trigonometry - Activity 21 General Triangle Solution: Given three sides.

Trigonometry - Activity 21 General Triangle Solution: Given three sides. Nme: lss: p 43 Mths Helper Plus Resoure Set. opyright 003 rue. Vughn, Tehers hoie Softwre Trigonometry - tivity 1 Generl Tringle Solution: Given three sides. When the three side lengths '', '' nd '' of

More information

Fall 2016 Social Sciences 7418 University of Wisconsin-Madison. Transactions and Portfolio Crowding Out

Fall 2016 Social Sciences 7418 University of Wisconsin-Madison. Transactions and Portfolio Crowding Out Economcs 435 Menze D. Cnn Fall 6 Socal Scences 748 Unversty of Wsconsn-Madson. Standard IS-LM Transactons and ortfolo Crowdng Out Transactons crowdng out of nvestment s te reducton n nvestment attrbutable

More information

UNIVERSITY OF BOLTON WESTERN INTERNATIONAL COLLEGE, RAS AL KHAIMAH BENG(HONS) MECHANICAL ENGINEERING SEMESTER TWO EXAMINATION 2014/2015

UNIVERSITY OF BOLTON WESTERN INTERNATIONAL COLLEGE, RAS AL KHAIMAH BENG(HONS) MECHANICAL ENGINEERING SEMESTER TWO EXAMINATION 2014/2015 OCD5 UNIVERSITY OF BOLTON WESTERN INTERNATIONAL COLLEGE, RAS AL KHAIMAH BENG(HONS) MECHANICAL ENGINEERING SEMESTER TWO EXAMINATION 0/05 FINITE ELEMENT AND DIFFERENCE SOLUTIONS MODULE NO: AME6006 Date:

More information

INF 4130 Exercise set 4

INF 4130 Exercise set 4 INF 4130 Exercise set 4 Exercise 1 List the order in which we extrct the nodes from the Live Set queue when we do redth first serch of the following grph (tree) with the Live Set implemented s LIFO queue.

More information

Pyramid algorithms for barycentric rational interpolation

Pyramid algorithms for barycentric rational interpolation Pyrmd lgorthms for rycentrc rtonl nterpolton K Hormnn Scott Schefer Astrct We present new perspectve on the Floter Hormnn nterpolnt Ths nterpolnt s rtonl of degree (n, d ), reproduces polynomls of degree

More information

2.21 The Medical Care Plan Beneficiary Registration System. Introduction

2.21 The Medical Care Plan Beneficiary Registration System. Introduction 2.21 Te Medical Care Plan Beneficiary Registration System Introduction Te Newfoundland Medical Care Plan (MCP) was introduced in Newfoundland and Labrador on 1 April 1969. It is a plan of medical care

More information

Long-term Memory Review PROFICIENCY PRACTICE: MONDAY REVIEW

Long-term Memory Review PROFICIENCY PRACTICE: MONDAY REVIEW PROFICINCY PRACTIC: MONDAY RVIW : A D 14 cm B 21 cm C 2) Use : The tringles in the figure ove re similr. ) nd re mesures of corresponding sides. ) nd re mesures of nother pir of corresponding sides. 3)

More information

NBER WORKING PAPER SERIES DEBT FINANCING IN ASSET MARKETS. Zhiguo He Wei Xiong. Working Paper

NBER WORKING PAPER SERIES DEBT FINANCING IN ASSET MARKETS. Zhiguo He Wei Xiong. Working Paper NBER WORKING PAPER SERIES DEBT FINANCING IN ASSET MARKETS Ziguo He Wei Xiong Working Paper 17935 ttp//www.nber.org/papers/w17935 NATIONAL BUREAU OF ECONOMIC RESEARCH 15 Massacusetts Avenue Cambrige, MA

More information

3: Central Limit Theorem, Systematic Errors

3: Central Limit Theorem, Systematic Errors 3: Central Lmt Theorem, Systematc Errors 1 Errors 1.1 Central Lmt Theorem Ths theorem s of prme mportance when measurng physcal quanttes because usually the mperfectons n the measurements are due to several

More information

Dynamic power control in a fading downlink channel subject to an energy constraint

Dynamic power control in a fading downlink channel subject to an energy constraint Queueng Sst 2007) 55:41 69 DOI 10.1007/s11134-006-9004-7 Dnamc power contro n a fadng downnk canne subject to an energ constrant Barış Ata. Konstantnos E. Zacarads Receved: 9 October 2005 / Revsed: 1 October

More information

Loading Factors and Equilibria in Insurance Markets

Loading Factors and Equilibria in Insurance Markets Loading Factors and Equiibria in Insurance Markets Yoram Eden, * Eiakim Katz, ** and Jacob Rosenberg *** Abstract: Tis paper examines te effect of introducing positive oading factors into insurance premia,

More information

b. (6 pts) State the simple linear regression models for these two regressions: Y regressed on X, and Z regressed on X.

b. (6 pts) State the simple linear regression models for these two regressions: Y regressed on X, and Z regressed on X. Mat 46 Exam Sprg 9 Mara Frazer Name SOLUTIONS Solve all problems, ad be careful ot to sped too muc tme o a partcular problem. All ecessary SAS fles are our usual folder (P:\data\mat\Frazer\Regresso). You

More information

Exercise 1: Robinson Crusoe who is marooned on an island in the South Pacific. He can grow bananas and coconuts. If he uses

Exercise 1: Robinson Crusoe who is marooned on an island in the South Pacific. He can grow bananas and coconuts. If he uses Jon Riley F Maimization wit a single constraint F5 Eercises Eercise : Roinson Crusoe wo is marooned on an isl in te Sout Pacific He can grow ananas coconuts If e uses z acres to produce ananas z acres

More information

Bargaining in Standing Committees with an Endogenous Default

Bargaining in Standing Committees with an Endogenous Default Barganng n Standng Commttees wt an Endogenous Default Vncent Anes Unversty of Nottngam Danel J. Sedmann Unversty of Nottngam July 7, 2014 Abstract Commttee votng as mostly been nvestgated from te perspectve

More information

Spring 2018 Social Sciences 7418 University of Wisconsin-Madison. Transactions and Portfolio Crowding Out

Spring 2018 Social Sciences 7418 University of Wisconsin-Madison. Transactions and Portfolio Crowding Out Economcs 44 Menze D. Cnn Sprng 8 Socal Scences 748 Unversty of Wsconsn-Madson. Standard IS-LM Transactons and Portfolo Crowdng Out Transactons crowdng out of nvestment s te reducton n nvestment attrbutable

More information

Chapter 5 Student Lecture Notes 5-1

Chapter 5 Student Lecture Notes 5-1 Chapter 5 Student Lecture Notes 5-1 Basc Busness Statstcs (9 th Edton) Chapter 5 Some Important Dscrete Probablty Dstrbutons 004 Prentce-Hall, Inc. Chap 5-1 Chapter Topcs The Probablty Dstrbuton of a Dscrete

More information

Bargaining in Standing Committees with an Endogenous Default

Bargaining in Standing Committees with an Endogenous Default Barganng n Standng Commttees wt an Endogenous Default Vncent Anes Unversty of Nottngam Danel J. Sedmann Unversty of Nottngam August 15, 2013 Abstract Commttee votng as mostly been nvestgated from te perspectve

More information

1 Introducton Opton prcng teory as been te core of modern matematcal nance snce te dervaton of te famous Blac-Scoles (19) formula wc provdes a partal

1 Introducton Opton prcng teory as been te core of modern matematcal nance snce te dervaton of te famous Blac-Scoles (19) formula wc provdes a partal CIT-CDS - Dstrbuton-Based Opton Prcng on Lattce Asset Dynamcs Models Yuj YAMADA y James A PRIMBS z Control and Dynamcal Systems 1-81 Calforna Insttute of Tecnology Pasadena, CA 911, USA August, Abstract

More information

2017 Year-End Retirement Action Plan

2017 Year-End Retirement Action Plan 2017 Year-End Retirement Action Plan Te end of te year is a good time to assess your overall financial picture, especially your retirement strategy. As te year comes to a close, use tis action plan to

More information

DATABASE-ASSISTED spectrum sharing is a promising

DATABASE-ASSISTED spectrum sharing is a promising 1 Optimal Pricing and Admission Control for Heterogeneous Secondary Users Cangkun Jiang, Student Member, IEEE, Lingjie Duan, Member, IEEE, and Jianwei Huang, Fellow, IEEE Abstract Tis paper studies ow

More information

Future value of an annuity

Future value of an annuity Announcements The secon hour-exam wll be hel on Fray, July 12. The use of cell phones an other wreless evces s not permtte on the exam. You wll nee to brng a separate calculator for the exam. Sharng of

More information

Calculus I Homework: Four Ways to Represent a Function Page 1. where h 0 and f(x) = x x 2.

Calculus I Homework: Four Ways to Represent a Function Page 1. where h 0 and f(x) = x x 2. Calculus I Homework: Four Ways to Represent a Function Page 1 Questions Example Find f(2 + ), f(x + ), and f(x + ) f(x) were 0 and f(x) = x x 2. Example Find te domain and sketc te grap of te function

More information

Task Force on quality of business survey data

Task Force on quality of business survey data Fnal Report V -.. 3 Task Force on qualty of busness survey data Task force 5: wegtng approaces . Introducton Busness tendency surveys (BS) dffer from most busness surveys by ter early release, te qualtatve

More information

Chapter - IV. Total and Middle Fuzzy Graph

Chapter - IV. Total and Middle Fuzzy Graph Chapter - IV otal and Mddle Fuzzy Graph CHAPER - IV OAL AND MIDDLE FUZZY GRAPH In ths chapter for the gven fuzzy graph G:(σ, µ), subdvson fuzzy graph sd(g) : ( σ sd, µ sd ), square fuzzy graph S 2 ( G)

More information

Labor Market Flexibility and Growth.

Labor Market Flexibility and Growth. Labor Market Flexibility and Growt. Enisse Karroubi July 006. Abstract Tis paper studies weter exibility on te labor market contributes to output growt. Under te assumption tat rms and workers face imperfect

More information

CH 71 COMPLETING THE SQUARE INTRODUCTION FACTORING PERFECT SQUARE TRINOMIALS

CH 71 COMPLETING THE SQUARE INTRODUCTION FACTORING PERFECT SQUARE TRINOMIALS CH 7 COMPLETING THE SQUARE INTRODUCTION I t s now time to py our dues regrding the Qudrtic Formul. Wht, you my sk, does this men? It mens tht the formul ws merely given to you once or twice in this course,

More information

15-451/651: Design & Analysis of Algorithms January 22, 2019 Lecture #3: Amortized Analysis last changed: January 18, 2019

15-451/651: Design & Analysis of Algorithms January 22, 2019 Lecture #3: Amortized Analysis last changed: January 18, 2019 5-45/65: Desgn & Analyss of Algorthms January, 09 Lecture #3: Amortzed Analyss last changed: January 8, 09 Introducton In ths lecture we dscuss a useful form of analyss, called amortzed analyss, for problems

More information

This paper is not to be removed from the Examination Halls UNIVERSITY OF LONDON

This paper is not to be removed from the Examination Halls UNIVERSITY OF LONDON ~~FN3092 ZA 0 his pper is not to be remove from the Exmintion Hlls UNIESIY OF LONDON FN3092 ZA BSc egrees n Diploms for Grutes in Economics, Mngement, Finnce n the Socil Sciences, the Diploms in Economics

More information

Number of women 0.15

Number of women 0.15 . Grouped Data (a Mdponts Trmester (months Number o women Relatve Frequency Densty.5 [0, 3 40 40/400 = 0.60 0.60/3 = 0. 4.5 [3, 6 60 60/400 = 0.5 0.5/3 = 0.05 7.5 [6, 9 00 00/400 = 0.5 0.5/3 = 0.0833 0.60

More information

Elton, Gruber, Brown, and Goetzmann. Modern Portfolio Theory and Investment Analysis, 7th Edition. Solutions to Text Problems: Chapter 9

Elton, Gruber, Brown, and Goetzmann. Modern Portfolio Theory and Investment Analysis, 7th Edition. Solutions to Text Problems: Chapter 9 Elton, Gruber, Brown, and Goetzmann Modern Portfolo Theory and Investment Analyss, 7th Edton Solutons to Text Problems: Chapter 9 Chapter 9: Problem In the table below, gven that the rskless rate equals

More information

Dynamic model of funding in interbank payment systems

Dynamic model of funding in interbank payment systems 5 th Bn of Fnlnd s Pyment nd Settlement Smulton Semnr August 2007 Dscusson of Mrco Glbt nd Kmmo Sormä s Dynmc model of fundng n nterbn pyment systems By Fben Renult (Bnque de Frnce) The vews expressed

More information

Lecture 7. We now use Brouwer s fixed point theorem to prove Nash s theorem.

Lecture 7. We now use Brouwer s fixed point theorem to prove Nash s theorem. Topcs on the Border of Economcs and Computaton December 11, 2005 Lecturer: Noam Nsan Lecture 7 Scrbe: Yoram Bachrach 1 Nash s Theorem We begn by provng Nash s Theorem about the exstance of a mxed strategy

More information

Market Competition, Institutions, and Contracting. Draft: Not for Citation or Circulation

Market Competition, Institutions, and Contracting. Draft: Not for Citation or Circulation Market Competton, Insttutons, and Contractng Prelmnary Draft Prepared for Presentaton, Department of Agrcultural and Appled Economcs, Unversty of Wsconsn September 18, 009 Draft: Not for Ctaton or Crculaton

More information

Advanced Microeconomics(ECH 32306)

Advanced Microeconomics(ECH 32306) Advanced Microeconomics(ECH 6) Homeork --- Soutions Expected Utiity Teory On p Jee and Reny say tat AXIOM G4 (Monotonicity) impies a an Prove tis We prove tis by contradiction Suppose a an, ten a a n and

More information

MARKET EQUILIBRIUM UNDER THE CIRCUMSTANCES OF SELECTABLE ECONOMIC CONDITIONS. Osamu Keida

MARKET EQUILIBRIUM UNDER THE CIRCUMSTANCES OF SELECTABLE ECONOMIC CONDITIONS. Osamu Keida MARKET EQUILIBRIUM UNDER THE CIRCUMSTANCES OF SELECTABLE ECONOMIC CONDITIONS Osamu Keida WP-AD 2006-02 Correspondence: Kumamoto Gakuen University (E-mai:keida@kumagaku.ac.jp) Editor: Instituto Vaenciano

More information

MOBILE computing and the World Wide Web (WWW)

MOBILE computing and the World Wide Web (WWW) Word Academy of Scence, Engneerng and Tecnoogy Internatona Jorna of Compter and Informaton Engneerng Vo:3, No:4, 009 A Serazabty Condton for Mt-step Transactons Accessng Ordered Data Rafat Asorman, Water

More information

332 Mathematical Induction Solutions for Chapter 14. for every positive integer n. Proof. We will prove this with mathematical induction.

332 Mathematical Induction Solutions for Chapter 14. for every positive integer n. Proof. We will prove this with mathematical induction. 33 Mathematcal Inducton. Solutons for Chapter. Prove that 3 n n n for every postve nteger n. Proof. We wll prove ths wth mathematcal nducton. Observe that f n, ths statement s, whch s obvously true. Consder

More information

Finite difference method for the Black and Scholes PDE (TP-1)

Finite difference method for the Black and Scholes PDE (TP-1) Numerical metods for PDE in Finance - ENSTA - S1-1/MMMEF Finite difference metod for te Black and Scoles PDE (TP-1) November 2015 1 Te Euler Forward sceme We look for a numerical approximation of te European

More information

ECE 586GT: Problem Set 2: Problems and Solutions Uniqueness of Nash equilibria, zero sum games, evolutionary dynamics

ECE 586GT: Problem Set 2: Problems and Solutions Uniqueness of Nash equilibria, zero sum games, evolutionary dynamics Unversty of Illnos Fall 08 ECE 586GT: Problem Set : Problems and Solutons Unqueness of Nash equlbra, zero sum games, evolutonary dynamcs Due: Tuesday, Sept. 5, at begnnng of class Readng: Course notes,

More information

Released Assessment Questions, 2017 QUESTIONS

Released Assessment Questions, 2017 QUESTIONS Relese Assessment Questions, 2017 QUESTIONS Gre 9 Assessment of Mthemtis Applie Re the instrutions elow. Along with this ooklet, mke sure you hve the Answer Booklet n the Formul Sheet. You my use ny spe

More information

2.17 Tax Expenditures. Introduction. Scope and Objectives

2.17 Tax Expenditures. Introduction. Scope and Objectives Introduction Programs offered by te Province are normally outlined in te Estimates and approved by te Members of te House of Assembly as part of te annual budgetary approval process. However, te Province

More information

by open ascending bid ("English") auction Auctioneer raises asking price until all but one bidder drops out

by open ascending bid (English) auction Auctioneer raises asking price until all but one bidder drops out Auctions. Auction off a single item (a) () (c) (d) y open ascending id ("English") auction Auctioneer raises asking price until all ut one idder drops out y Dutch auction (descending asking price) Auctioneer

More information

2) In the medium-run/long-run, a decrease in the budget deficit will produce:

2) In the medium-run/long-run, a decrease in the budget deficit will produce: 4.02 Quz 2 Solutons Fall 2004 Multple-Choce Questons ) Consder the wage-settng and prce-settng equatons we studed n class. Suppose the markup, µ, equals 0.25, and F(u,z) = -u. What s the natural rate of

More information

NBER WORKING PAPER SERIES CRASHES AND RECOVERIES IN ILLIQUID MARKETS. Ricardo Lagos Guillaume Rocheteau Pierre-Olivier Weill

NBER WORKING PAPER SERIES CRASHES AND RECOVERIES IN ILLIQUID MARKETS. Ricardo Lagos Guillaume Rocheteau Pierre-Olivier Weill NBER WORKING PAPER SERIES CRASHES AND RECOVERIES IN ILLIQUID MARKETS Rcardo Lagos Gullaume Roceteau Perre-Olver Well Workng Paper 14119 ttp://www.nber.org/papers/w14119 NATIONAL BUREAU OF ECONOMIC RESEARCH

More information

Labor Market Flexibility and Growth.

Labor Market Flexibility and Growth. Labor Market Flexibility and Growt. Enisse Karroubi May 9, 006. Abstract Tis paper studies weter exibility on te labor market contributes to output growt. First I document two stylized facts concerning

More information

The New Circus. Main ideas are the most important ideas in a passage. They are the messages the writer

The New Circus. Main ideas are the most important ideas in a passage. They are the messages the writer The New Cirus SUBJECT READING SKILL TEXT TYPE Culture n People Fining min ies n etils Content-se pssge Fining min ies n etils Min ies re the most importnt ies in pssge. They re the messges the writer wnts

More information

Optimum thresholding using mean and conditional mean square error

Optimum thresholding using mean and conditional mean square error Optmum tresoldng usng mean and condtonal mean square error José E. Fgueroa-López and Cecla Mancn February 8, 7 Abstract We consder a unvarate semmartngale model for te logartm of an asset prce, contanng

More information

Elements of Economic Analysis II Lecture VI: Industry Supply

Elements of Economic Analysis II Lecture VI: Industry Supply Elements of Economc Analyss II Lecture VI: Industry Supply Ka Hao Yang 10/12/2017 In the prevous lecture, we analyzed the frm s supply decson usng a set of smple graphcal analyses. In fact, the dscusson

More information

(a) by substituting u = x + 10 and applying the result on page 869 on the text, (b) integrating by parts with u = ln(x + 10), dv = dx, v = x, and

(a) by substituting u = x + 10 and applying the result on page 869 on the text, (b) integrating by parts with u = ln(x + 10), dv = dx, v = x, and Supplementry Questions for HP Chpter 5. Derive the formul ln( + 0) d = ( + 0) ln( + 0) + C in three wys: () by substituting u = + 0 nd pplying the result on pge 869 on the tet, (b) integrting by prts with

More information

Complex Survey Sample Design in IRS' Multi-objective Taxpayer Compliance Burden Studies

Complex Survey Sample Design in IRS' Multi-objective Taxpayer Compliance Burden Studies Complex Survey Sample Design in IRS' Multi-objective Taxpayer Compliance Burden Studies Jon Guyton Wei Liu Micael Sebastiani Internal Revenue Service, Office of Researc, Analysis & Statistics 1111 Constitution

More information

TCOM501 Networking: Theory & Fundamentals Final Examination Professor Yannis A. Korilis April 26, 2002

TCOM501 Networking: Theory & Fundamentals Final Examination Professor Yannis A. Korilis April 26, 2002 TO5 Networng: Theory & undamentals nal xamnaton Professor Yanns. orls prl, Problem [ ponts]: onsder a rng networ wth nodes,,,. In ths networ, a customer that completes servce at node exts the networ wth

More information

Bundling and Competition for Slots: On the Portfolio E ects of Bundling

Bundling and Competition for Slots: On the Portfolio E ects of Bundling Bundlng and Competton for Slots: On te Portfolo E ects of Bundlng Do-Sn Jeon y and Domenco Mencucc z February 11, 2009 Abstract We consder competton among n sellers wen eac of tem sells a portfolo of dstnct

More information

What is International Strategic Financial Planning (ISFP)?

What is International Strategic Financial Planning (ISFP)? Wat is International Strategic Financial Planning ()? Spring 2013 Wy do we need? Wat do we do in Finance? We evaluate and manage te timing and predictability of cas in- and outflows related to a corporation's

More information

Random Variables. 8.1 What is a Random Variable? Announcements: Chapter 8

Random Variables. 8.1 What is a Random Variable? Announcements: Chapter 8 Announcements: Quz starts after class today, ends Monday Last chance to take probablty survey ends Sunday mornng. Next few lectures: Today, Sectons 8.1 to 8. Monday, Secton 7.7 and extra materal Wed, Secton

More information

OCR Statistics 1 Working with data. Section 2: Measures of location

OCR Statistics 1 Working with data. Section 2: Measures of location OCR Statstcs 1 Workng wth data Secton 2: Measures of locaton Notes and Examples These notes have sub-sectons on: The medan Estmatng the medan from grouped data The mean Estmatng the mean from grouped data

More information

Optimization based Option Pricing Bounds via Piecewise Polynomial Super- and Sub-Martingales

Optimization based Option Pricing Bounds via Piecewise Polynomial Super- and Sub-Martingales 28 American Control Conference Westin Seattle Hotel, Seattle, Wasington, USA June 11-13, 28 WeA1.6 Optimization based Option Pricing Bounds via Piecewise Polynomial Super- and Sub-Martingales James A.

More information

The study guide does not look exactly like the exam but it will help you to focus your study efforts.

The study guide does not look exactly like the exam but it will help you to focus your study efforts. Mat 0 Eam Study Guide Solutions Te study guide does not look eactly like te eam but it will elp you to focus your study efforts. Here is part of te list of items under How to Succeed in Mat 0 tat is on

More information

Ratio and Proportion Long-Term Memory Review Day 1 - Review

Ratio and Proportion Long-Term Memory Review Day 1 - Review Rtio nd Proportion Dy 1 - Review 1. Provide omplete response to eh of the following: ) A rtio ompres two. ) A proportion sets two rtios to eh other. ) Wht re similr figures? 2. Drw two similr figures.

More information

Mathematical Thinking Exam 1 09 October 2017

Mathematical Thinking Exam 1 09 October 2017 Mathematcal Thnkng Exam 1 09 October 2017 Name: Instructons: Be sure to read each problem s drectons. Wrte clearly durng the exam and fully erase or mark out anythng you do not want graded. You may use

More information

Dr. A. Sudhakaraiah* V. Rama Latha E.Gnana Deepika

Dr. A. Sudhakaraiah* V. Rama Latha E.Gnana Deepika Internatonal Journal Of Scentfc & Engneerng Research, Volume, Issue 6, June-0 ISSN - Splt Domnatng Set of an Interval Graph Usng an Algorthm. Dr. A. Sudhakaraah* V. Rama Latha E.Gnana Deepka Abstract :

More information

Hardware-Software Cosynthesis of Multi-Mode Multi-Task Embedded Systems with Real-Time Constraints

Hardware-Software Cosynthesis of Multi-Mode Multi-Task Embedded Systems with Real-Time Constraints Hardware-Software Cosyntess of Mult-Mode Mult-Task Embedded Systems wt Real-Tme Constrants Hyunok O Soono Ha Te Scool of Electrcal Engneerng and Computer Scence Seoul Natonal Unversty Seoul 151-742, KOREA

More information

Finite Math - Fall Section Future Value of an Annuity; Sinking Funds

Finite Math - Fall Section Future Value of an Annuity; Sinking Funds Fnte Math - Fall 2016 Lecture Notes - 9/19/2016 Secton 3.3 - Future Value of an Annuty; Snkng Funds Snkng Funds. We can turn the annutes pcture around and ask how much we would need to depost nto an account

More information

AMERICAN DEPOSITARY RECEIPTS. ISFP Stephen Sapp

AMERICAN DEPOSITARY RECEIPTS. ISFP Stephen Sapp AMERICAN DEPOSITARY RECEIPTS Stepen Sapp Definition: ADRs American Depositary Receipts (ADRs) are dollardenominated negotiable securities representing a sare of a non-us company. Tis security trades and

More information

YORK UNIVERSITY Faculty of Science Department of Mathematics and Statistics MATH A Test #2 November 03, 2014

YORK UNIVERSITY Faculty of Science Department of Mathematics and Statistics MATH A Test #2 November 03, 2014 Famly Name prnt): YORK UNIVERSITY Faculty of Scence Department of Mathematcs and Statstcs MATH 2280.00 A Test #2 November 0, 2014 Solutons Gven Name: Student No: Sgnature: INSTRUCTIONS: 1. Please wrte

More information