EXERCISES PART I ANSWERS

Size: px
Start display at page:

Download "EXERCISES PART I ANSWERS"

Transcription

1 UNIVERSIDADE CATÓLICA PORTUGUESA Faculdade de Ciências Econóicas e Eresariais MICROECONOMICS II nd seester 006/007 EXERCISES PART I ANSWERS Fernando Branco Carolina Reis

2 . Introduction. Preferences and utilit function Solved in class.. Consuer s coice and deand ) ) 3) z No ótio: TMS 0 0 TMS TMS 4) 0 5 5) ) ) + TE 0077 TE TE q 8) b q a b 9) ; ; d) 0 90 e) 36

3 f) * * A B 75 6 C D 4 6 0) ) ) d) 5 05 > e) f) TMS A- Ordinar Good B- Ordinar Good C- Ordinar Good D- Perfectl Inelastic Deand E- Ordinar Good A- Substitute Goods B- Unrelated C- Coleentar Goods D- Coleentar Goods E- Coleentar Goods 4 TMS B O t t 3) Bot would accet te ecange in bot circustances. 4) 0 3; 7 3 0; /7 < 4 0 3

4 5) i) 846 ii) 48 6 P.3 Substitution and Incoe Effects ) ) 3) 4) SE -565 IE SE - IE -3 Yes. d) U T 03 U J 0(3) kf T F d) F e) T Inferior Good IE: Noral Good IE: Ordinar Good TE: Inferior Good IE: Giffen Good TE: 5) Not necessaril it deends on te IE. 6) SE -565 IE

5 P P U P P U d) SE -35 IE -8 7) 8) T 9) T F d) F 05 3 (6) 95 8 U > U 0) 055(9) > 0 Te goods classification would cange.. Dualit Consuer Teor ) VER: α α ; - d) α eu ( ) U ln + α α α α ; U α ln α e) α ; α α ; U α ln α 5

6 ) v ( ) ln + α α α eu ( ) U ln + α α α γ γ v γ γ 3) 4) - e U γ γ d) w γ γ γ w γ γ e) IOC: γ f) - POC: d d U 0 ( γ ) 04; 5 ; 6 5) He cannot be aiizing Utilit in bot cases. 6) 7) 8) 0 a ; 0 b ; a+ b ab05 b b + a ab v b + a U a a b + a U b 6

7 9) e U + a b a IOC: b a > ; 0 b a < 0; b a b a b v a a U ; 0 b a > a U < 0; b b a U a b b b e a U in a > VER: 0 b a b 0) b < VER : 0 3. Toics in Consuer Teor 3. Te sul of labor ) Otial Coice: 9; l C + 7w 7

8 ) - 3) 4) Yes it is ossible tat Jon decides not to work. He will work ore in Setúbal. d) He igt decide to work or not to work. Eiter wa e will be worse off. - wt X z * ( w) w X w T d) < 0 zx e) X wt X X wt Otial Coice: l 8; z 8 New budget line: c+ 5l 0 Otial Coice: l 7; z 9 5) Otial Coice: l 8; c 84; z 3 Corner Solution: l 35; c 65; z 75 6) Tere is onl a substitution effect. Unless references are Leontief Melissa will cange er decision in wic case se will be better off. 7) It deends on references. 8) s z T 0 z w d) * z * z * z ) s z T( α) α w X s ( α) w z > 0 X < T α α X w T ( α) 8

9 zw zx α X w( α) T αx α X w( α) T αx 3. Interteoral Consution ) C 4(54); C 84 3 ( C ) 5 ( + r) 5 * * * 3 ( C) ( C ) 5 5 ( + r) d) r 50% e) C 0; C 89 f) TMS ( + r) TMS > ( + r) g) r 0% TMS ( + r) ) Not necessaril. 3) He will accet rojects if z X > ( + r). 4) Possible Corner Solutions: C Y; C C 0 C 0 Y 3.3 Revealed Preference ) Preferences are not transitive. ) Not consistent. Consistent. 3) It is consistent wit WARP. 4) Situation 3: 9

10 4 Situation : 0; Yes. An oint in te BC: Welfare Measure ) CV 396 EV 4 CSV 773 CV 60 EV 5 CSV 90 ) 3) EV 99 Laseres Incoe Variation 50 (Slutsk Coensation) Minial aount EV 607 Subsid Paasce Incoe Variation 40 CV 63 Ta Laseres Incoe Variation 8 CSV 609 d) Quasi-linear Preferences: Good as no IE. 4) ( U ) ( U ) 0 Tus: CV EV CSV 6 EV Paasce Incoe Variation 36(36) CV Laseres Incoe Variation 6(6) CSV 305 d) Leontief Preferences: no SE. Hicksian deand curves are vertical lines. 5) T F 0

11 6) 7) Deends on te tariff. Tariff U 598 > 580 Te consuers will agree wit te councilor s idea. - Indeendent Councilor: (Laseres) incoe variation 9 - Maor: Incoe variation 5 Te refer to vote for te indeendent councilor. d) A 08 A

INCOME AND SUBSTITUTION EFFECTS. Two Demand Functions CHANGES IN INCOME. [See Chapter 5 and 6]

INCOME AND SUBSTITUTION EFFECTS. Two Demand Functions CHANGES IN INCOME. [See Chapter 5 and 6] INCOME AND SUBSTITUTION EFFECTS [See Chater 5 and 6] Two Deand Functions Marshallian deand i ( n describes how consution varies with rices and incoe. Obtained by aiizing utility subject to the budget constraint.

More information

Your Suggestions. Board/slides. Too fast/too slow. Book does not have enough examples.

Your Suggestions. Board/slides. Too fast/too slow. Book does not have enough examples. Your Suggestions Sale robles and eales in lecture. Donload recitation robles before recitation. Colete eercises in recitations. Reorganize eb site. Have oer oint slides available earlier. Overvie class

More information

Section 2.1 The Definition of the Derivative. We are interested in finding the slope of the tangent line at a specific point.

Section 2.1 The Definition of the Derivative. We are interested in finding the slope of the tangent line at a specific point. Popper 6: Review of skills: Find tis difference quotient. f ( x ) f ( x) if f ( x) x Answer coices given in audio on te video. Section.1 Te Definition of te Derivative We are interested in finding te slope

More information

Logarithmic functions

Logarithmic functions Roberto s Notes on Differential Calculus Capter 5: Derivatives of transcendental functions Section Derivatives of Logaritmic functions Wat ou need to know alread: Definition of derivative and all basic

More information

Equilibrium and Pareto Efficiency in an exchange economy

Equilibrium and Pareto Efficiency in an exchange economy Microeconomic Teory -1- Equilibrium and efficiency Equilibrium and Pareto Efficiency in an excange economy 1. Efficient economies 2 2. Gains from excange 6 3. Edgewort-ox analysis 15 4. Properties of a

More information

Intermediate microeconomics. Lecture 2: Consumer Theory II: demand. Varian, chapters 6, 8, 9

Intermediate microeconomics. Lecture 2: Consumer Theory II: demand. Varian, chapters 6, 8, 9 Interediate icroeconoics Lecture 2: Consuer Theory II: deand. Varian, chapters 6, 8, 9 Agenda 1. Noral and inferior goods 2. Incoe offer curves and Engel curves 3. Ordinary goods and Giffen goods 4. Price

More information

3.2 THE FUNDAMENTAL WELFARE THEOREMS

3.2 THE FUNDAMENTAL WELFARE THEOREMS Essential Microeconomics -1-3.2 THE FUNDMENTL WELFRE THEOREMS Walrasian Equilibrium 2 First welfare teorem 3 Second welfare teorem (conve, differentiable economy) 12 Te omotetic preference 2 2 economy

More information

Walrasian Equilibrium in an exchange economy

Walrasian Equilibrium in an exchange economy Microeconomic Teory -1- Walrasian equilibrium Walrasian Equilibrium in an ecange economy 1. Homotetic preferences 2 2. Walrasian equilibrium in an ecange economy 11 3. Te market value of attributes 18

More information

3. THE EXCHANGE ECONOMY

3. THE EXCHANGE ECONOMY Essential Microeconomics -1-3. THE EXCHNGE ECONOMY Pareto efficient allocations 2 Edgewort box analysis 5 Market clearing prices 13 Walrasian Equilibrium 16 Equilibrium and Efficiency 22 First welfare

More information

FOCUS ON THEORY. We recall that a function g(x) is differentiable at the point a if the limit

FOCUS ON THEORY. We recall that a function g(x) is differentiable at the point a if the limit FOCUS ON THEORY 653 DIFFERENTIABILITY Notes on Differentiabilit In Section 13.3 we gave an informal introduction to te concet of differentiabilit. We called a function f (; ) differentiable at a oint (a;

More information

Essential Microeconomics : EQUILIBRIUM AND EFFICIENCY WITH PRODUCTION Key ideas: Walrasian equilibrium, first and second welfare theorems

Essential Microeconomics : EQUILIBRIUM AND EFFICIENCY WITH PRODUCTION Key ideas: Walrasian equilibrium, first and second welfare theorems Essential Microeconomics -- 5.2: EQUILIBRIUM AND EFFICIENCY WITH PRODUCTION Key ideas: Walrasian equilibrium, irst and second welare teorems A general model 2 First welare Teorem 7 Second welare teorem

More information

Continuity and Differentiability Worksheet

Continuity and Differentiability Worksheet Continuity and Differentiability Workseet (Be sure tat you can also do te grapical eercises from te tet- Tese were not included below! Typical problems are like problems -3, p. 6; -3, p. 7; 33-34, p. 7;

More information

Higher Derivatives. Differentiable Functions

Higher Derivatives. Differentiable Functions Calculus 1 Lia Vas Higer Derivatives. Differentiable Functions Te second derivative. Te derivative itself can be considered as a function. Te instantaneous rate of cange of tis function is te second derivative.

More information

The Derivative as a Function

The Derivative as a Function Section 2.2 Te Derivative as a Function 200 Kiryl Tsiscanka Te Derivative as a Function DEFINITION: Te derivative of a function f at a number a, denoted by f (a), is if tis limit exists. f (a) f(a + )

More information

Partial differentiation. Background mathematics review

Partial differentiation. Background mathematics review Partial differentiation Background mathematics review David Miller Partial differentiation Partial derivatives Background mathematics review David Miller Partial derivative Suppose we have a function f(,)

More information

University Mathematics 2

University Mathematics 2 University Matematics 2 1 Differentiability In tis section, we discuss te differentiability of functions. Definition 1.1 Differentiable function). Let f) be a function. We say tat f is differentiable at

More information

Combining functions: algebraic methods

Combining functions: algebraic methods Combining functions: algebraic metods Functions can be added, subtracted, multiplied, divided, and raised to a power, just like numbers or algebra expressions. If f(x) = x 2 and g(x) = x + 2, clearly f(x)

More information

. If lim. x 2 x 1. f(x+h) f(x)

. If lim. x 2 x 1. f(x+h) f(x) Review of Differential Calculus Wen te value of one variable y is uniquely determined by te value of anoter variable x, ten te relationsip between x and y is described by a function f tat assigns a value

More information

4. The slope of the line 2x 7y = 8 is (a) 2/7 (b) 7/2 (c) 2 (d) 2/7 (e) None of these.

4. The slope of the line 2x 7y = 8 is (a) 2/7 (b) 7/2 (c) 2 (d) 2/7 (e) None of these. Mat 11. Test Form N Fall 016 Name. Instructions. Te first eleven problems are wort points eac. Te last six problems are wort 5 points eac. For te last six problems, you must use relevant metods of algebra

More information

Part 2C. 3. Slutsky Equations Slutsky Slutsky Own-Price Effects

Part 2C. 3. Slutsky Equations Slutsky Slutsky Own-Price Effects Part 2C. Individual Demand Functions 3. Slutsk Equations Slutsk 方程式 Own-Price Effects A Slutsk Decomposition Cross-Price Effects Dualit and the Demand Concepts 2014.11.20 1 Own-Price Effects Q: What happens

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 6. Differential Calculus 6.. Differentiation from First Principles. In tis capter, we will introduce

More information

The Derivative The rate of change

The Derivative The rate of change Calculus Lia Vas Te Derivative Te rate of cange Knowing and understanding te concept of derivative will enable you to answer te following questions. Let us consider a quantity wose size is described by

More information

4.2 - Richardson Extrapolation

4.2 - Richardson Extrapolation . - Ricardson Extrapolation. Small-O Notation: Recall tat te big-o notation used to define te rate of convergence in Section.: Definition Let x n n converge to a number x. Suppose tat n n is a sequence

More information

3.1 Extreme Values of a Function

3.1 Extreme Values of a Function .1 Etreme Values of a Function Section.1 Notes Page 1 One application of te derivative is finding minimum and maimum values off a grap. In precalculus we were only able to do tis wit quadratics by find

More information

MVT and Rolle s Theorem

MVT and Rolle s Theorem AP Calculus CHAPTER 4 WORKSHEET APPLICATIONS OF DIFFERENTIATION MVT and Rolle s Teorem Name Seat # Date UNLESS INDICATED, DO NOT USE YOUR CALCULATOR FOR ANY OF THESE QUESTIONS In problems 1 and, state

More information

Micro I. Lesson 5 : Consumer Equilibrium

Micro I. Lesson 5 : Consumer Equilibrium Microecono mics I. Antonio Zabalza. Universit of Valencia 1 Micro I. Lesson 5 : Consumer Equilibrium 5.1 Otimal Choice If references are well behaved (smooth, conve, continuous and negativel sloed), then

More information

MTH-112 Quiz 1 Name: # :

MTH-112 Quiz 1 Name: # : MTH- Quiz Name: # : Please write our name in te provided space. Simplif our answers. Sow our work.. Determine weter te given relation is a function. Give te domain and range of te relation.. Does te equation

More information

Section 15.6 Directional Derivatives and the Gradient Vector

Section 15.6 Directional Derivatives and the Gradient Vector Section 15.6 Directional Derivatives and te Gradient Vector Finding rates of cange in different directions Recall tat wen we first started considering derivatives of functions of more tan one variable,

More information

Test 2 Review. 1. Find the determinant of the matrix below using (a) cofactor expansion and (b) row reduction. A = 3 2 =

Test 2 Review. 1. Find the determinant of the matrix below using (a) cofactor expansion and (b) row reduction. A = 3 2 = Test Review Find te determinant of te matrix below using (a cofactor expansion and (b row reduction Answer: (a det + = (b Observe R R R R R R R R R Ten det B = (((det Hence det Use Cramer s rule to solve:

More information

Solution. Solution. f (x) = (cos x)2 cos(2x) 2 sin(2x) 2 cos x ( sin x) (cos x) 4. f (π/4) = ( 2/2) ( 2/2) ( 2/2) ( 2/2) 4.

Solution. Solution. f (x) = (cos x)2 cos(2x) 2 sin(2x) 2 cos x ( sin x) (cos x) 4. f (π/4) = ( 2/2) ( 2/2) ( 2/2) ( 2/2) 4. December 09, 20 Calculus PracticeTest s Name: (4 points) Find te absolute extrema of f(x) = x 3 0 on te interval [0, 4] Te derivative of f(x) is f (x) = 3x 2, wic is zero only at x = 0 Tus we only need

More information

232 Calculus and Structures

232 Calculus and Structures 3 Calculus and Structures CHAPTER 17 JUSTIFICATION OF THE AREA AND SLOPE METHODS FOR EVALUATING BEAMS Calculus and Structures 33 Copyrigt Capter 17 JUSTIFICATION OF THE AREA AND SLOPE METHODS 17.1 THE

More information

MAT 145. Type of Calculator Used TI-89 Titanium 100 points Score 100 possible points

MAT 145. Type of Calculator Used TI-89 Titanium 100 points Score 100 possible points MAT 15 Test #2 Name Solution Guide Type of Calculator Used TI-89 Titanium 100 points Score 100 possible points Use te grap of a function sown ere as you respond to questions 1 to 8. 1. lim f (x) 0 2. lim

More information

On the Concept of Returns to Scale: Revisited

On the Concept of Returns to Scale: Revisited 3 J. Asian Dev. Stud, Vol. 5, Issue, (Marc 206) ISSN 2304-375X On te Concept of Returns to Scale: Revisited Parvez Azim Abstract Tis paper sows w it is tat in Economics text books and literature we invariabl

More information

1 + t5 dt with respect to x. du = 2. dg du = f(u). du dx. dg dx = dg. du du. dg du. dx = 4x3. - page 1 -

1 + t5 dt with respect to x. du = 2. dg du = f(u). du dx. dg dx = dg. du du. dg du. dx = 4x3. - page 1 - Eercise. Find te derivative of g( 3 + t5 dt wit respect to. Solution: Te integrand is f(t + t 5. By FTC, f( + 5. Eercise. Find te derivative of e t2 dt wit respect to. Solution: Te integrand is f(t e t2.

More information

Solutions to Homework #05 MATH ln z 2 + x 2 1 = 2x2 z 2 + x 2 + ln z2 + x 2. = x. ln z 2 + x 2 2z z 2 + x 2 = 2xz

Solutions to Homework #05 MATH ln z 2 + x 2 1 = 2x2 z 2 + x 2 + ln z2 + x 2. = x. ln z 2 + x 2 2z z 2 + x 2 = 2xz Solutions to Homeork #05 MATH Kaai Section. (I) Exercise #. g x and g z : Product Rule: g x = x @ ln z + x + ln z + x @ [x] = x x z + x + ln z + x = x z + x + ln z + x x is eld constant. g z = x @ ln z

More information

FUNDAMENTAL ECONOMICS Vol. I - Walrasian and Non-Walrasian Microeconomics - Anjan Mukherji WALRASIAN AND NON-WALRASIAN MICROECONOMICS

FUNDAMENTAL ECONOMICS Vol. I - Walrasian and Non-Walrasian Microeconomics - Anjan Mukherji WALRASIAN AND NON-WALRASIAN MICROECONOMICS FUNDAMENTAL ECONOMICS Vol. I - Walrasian and Non-Walrasian Microeconomics - Anjan Mukerji WALRASIAN AND NON-WALRASIAN MICROECONOMICS Anjan Mukerji Center for Economic Studies and Planning, Jawaarlal Neru

More information

Continuity. Example 1

Continuity. Example 1 Continuity MATH 1003 Calculus and Linear Algebra (Lecture 13.5) Maoseng Xiong Department of Matematics, HKUST A function f : (a, b) R is continuous at a point c (a, b) if 1. x c f (x) exists, 2. f (c)

More information

MA2264 -NUMERICAL METHODS UNIT V : INITIAL VALUE PROBLEMS FOR ORDINARY DIFFERENTIAL. By Dr.T.Kulandaivel Department of Applied Mathematics SVCE

MA2264 -NUMERICAL METHODS UNIT V : INITIAL VALUE PROBLEMS FOR ORDINARY DIFFERENTIAL. By Dr.T.Kulandaivel Department of Applied Mathematics SVCE MA64 -NUMERICAL METHODS UNIT V : INITIAL VALUE PROBLEMS FOR ORDINARY DIFFERENTIAL EQUATIONS B Dr.T.Kulandaivel Department of Applied Matematics SVCE Numerical ordinar differential equations is te part

More information

10 Derivatives ( )

10 Derivatives ( ) Instructor: Micael Medvinsky 0 Derivatives (.6-.8) Te tangent line to te curve yf() at te point (a,f(a)) is te line l m + b troug tis point wit slope Alternatively one can epress te slope as f f a m lim

More information

WYSE Academic Challenge 2004 State Finals Mathematics Solution Set

WYSE Academic Challenge 2004 State Finals Mathematics Solution Set WYSE Academic Callenge 00 State Finals Matematics Solution Set. Answer: c. We ave a sstem of tree equations and tree unknowns. We ave te equations: x + + z 0, x + 6 + 7z 9600, and 7x + + z 90. Wen we solve,

More information

1. Which one of the following expressions is not equal to all the others? 1 C. 1 D. 25x. 2. Simplify this expression as much as possible.

1. Which one of the following expressions is not equal to all the others? 1 C. 1 D. 25x. 2. Simplify this expression as much as possible. 004 Algebra Pretest answers and scoring Part A. Multiple coice questions. Directions: Circle te letter ( A, B, C, D, or E ) net to te correct answer. points eac, no partial credit. Wic one of te following

More information

lecture 35: Linear Multistep Mehods: Truncation Error

lecture 35: Linear Multistep Mehods: Truncation Error 88 lecture 5: Linear Multistep Meods: Truncation Error 5.5 Linear ultistep etods One-step etods construct an approxiate solution x k+ x(t k+ ) using only one previous approxiation, x k. Tis approac enoys

More information

MATH1151 Calculus Test S1 v2a

MATH1151 Calculus Test S1 v2a MATH5 Calculus Test 8 S va January 8, 5 Tese solutions were written and typed up by Brendan Trin Please be etical wit tis resource It is for te use of MatSOC members, so do not repost it on oter forums

More information

Exponentials and Logarithms Review Part 2: Exponentials

Exponentials and Logarithms Review Part 2: Exponentials Eponentials and Logaritms Review Part : Eponentials Notice te difference etween te functions: g( ) and f ( ) In te function g( ), te variale is te ase and te eponent is a constant. Tis is called a power

More information

Developing Transfer Functions from Heat & Material Balances

Developing Transfer Functions from Heat & Material Balances Colorado Sool of Mine CHEN43 Stirred ank Heater Develoing ranfer untion from Heat & Material Balane Examle ranfer untion Stirred ank Heater,,, A,,,,, We will develo te tranfer funtion for a tirred tank

More information

Introduction to Machine Learning. Recitation 8. w 2, b 2. w 1, b 1. z 0 z 1. The function we want to minimize is the loss over all examples: f =

Introduction to Machine Learning. Recitation 8. w 2, b 2. w 1, b 1. z 0 z 1. The function we want to minimize is the loss over all examples: f = Introduction to Macine Learning Lecturer: Regev Scweiger Recitation 8 Fall Semester Scribe: Regev Scweiger 8.1 Backpropagation We will develop and review te backpropagation algoritm for neural networks.

More information

Name: Answer Key No calculators. Show your work! 1. (21 points) All answers should either be,, a (finite) real number, or DNE ( does not exist ).

Name: Answer Key No calculators. Show your work! 1. (21 points) All answers should either be,, a (finite) real number, or DNE ( does not exist ). Mat - Final Exam August 3 rd, Name: Answer Key No calculators. Sow your work!. points) All answers sould eiter be,, a finite) real number, or DNE does not exist ). a) Use te grap of te function to evaluate

More information

Chapter 2. Limits and Continuity 16( ) 16( 9) = = 001. Section 2.1 Rates of Change and Limits (pp ) Quick Review 2.1

Chapter 2. Limits and Continuity 16( ) 16( 9) = = 001. Section 2.1 Rates of Change and Limits (pp ) Quick Review 2.1 Capter Limits and Continuity Section. Rates of Cange and Limits (pp. 969) Quick Review..... f ( ) ( ) ( ) 0 ( ) f ( ) f ( ) sin π sin π 0 f ( ). < < < 6. < c c < < c 7. < < < < < 8. 9. 0. c < d d < c

More information

3. True. 7. True. 9. True 11. True 13. True. 11. a.

3. True. 7. True. 9. True 11. True 13. True. 11. a. EXPLORING CONCEPTS WITH TECHNOLOGY, Page. Use Dot mode. Enter te unction as Y X *X

More information

Chapter 6 In our starting model: There are 2 goods The prices and income are given This is a world without time (the consumer can t save)

Chapter 6 In our starting model: There are 2 goods The prices and income are given This is a world without time (the consumer can t save) Chater 6 In our starting odel: There are goods The rices and incoe are given This is a world without tie (the consuer can t save) (Consuer) Deand is deterined through UTILITY MAXIMISATION given: TASTES

More information

Chapters 19 & 20 Heat and the First Law of Thermodynamics

Chapters 19 & 20 Heat and the First Law of Thermodynamics Capters 19 & 20 Heat and te First Law of Termodynamics Te Zerot Law of Termodynamics Te First Law of Termodynamics Termal Processes Te Second Law of Termodynamics Heat Engines and te Carnot Cycle Refrigerators,

More information

Differential Calculus (The basics) Prepared by Mr. C. Hull

Differential Calculus (The basics) Prepared by Mr. C. Hull Differential Calculus Te basics) A : Limits In tis work on limits, we will deal only wit functions i.e. tose relationsips in wic an input variable ) defines a unique output variable y). Wen we work wit

More information

Recall from our discussion of continuity in lecture a function is continuous at a point x = a if and only if

Recall from our discussion of continuity in lecture a function is continuous at a point x = a if and only if Computational Aspects of its. Keeping te simple simple. Recall by elementary functions we mean :Polynomials (including linear and quadratic equations) Eponentials Logaritms Trig Functions Rational Functions

More information

1 Proving the Fundamental Theorem of Statistical Learning

1 Proving the Fundamental Theorem of Statistical Learning THEORETICAL MACHINE LEARNING COS 5 LECTURE #7 APRIL 5, 6 LECTURER: ELAD HAZAN NAME: FERMI MA ANDDANIEL SUO oving te Fundaental Teore of Statistical Learning In tis section, we prove te following: Teore.

More information

Solution for the Homework 4

Solution for the Homework 4 Solution for te Homework 4 Problem 6.5: In tis section we computed te single-particle translational partition function, tr, by summing over all definite-energy wavefunctions. An alternative approac, owever,

More information

Calculus I Practice Exam 1A

Calculus I Practice Exam 1A Calculus I Practice Exam A Calculus I Practice Exam A Tis practice exam empasizes conceptual connections and understanding to a greater degree tan te exams tat are usually administered in introductory

More information

(4.2) -Richardson Extrapolation

(4.2) -Richardson Extrapolation (.) -Ricardson Extrapolation. Small-O Notation: Recall tat te big-o notation used to define te rate of convergence in Section.: Suppose tat lim G 0 and lim F L. Te function F is said to converge to L as

More information

MAT Calculus for Engineers I EXAM #1

MAT Calculus for Engineers I EXAM #1 MAT 65 - Calculus for Engineers I EXAM # Instructor: Liu, Hao Honor Statement By signing below you conrm tat you ave neiter given nor received any unautorized assistance on tis eam. Tis includes any use

More information

2.4 Exponential Functions and Derivatives (Sct of text)

2.4 Exponential Functions and Derivatives (Sct of text) 2.4 Exponential Functions an Derivatives (Sct. 2.4 2.6 of text) 2.4. Exponential Functions Definition 2.4.. Let a>0 be a real number ifferent tan. Anexponential function as te form f(x) =a x. Teorem 2.4.2

More information

Section 2.7 Derivatives and Rates of Change Part II Section 2.8 The Derivative as a Function. at the point a, to be. = at time t = a is

Section 2.7 Derivatives and Rates of Change Part II Section 2.8 The Derivative as a Function. at the point a, to be. = at time t = a is Mat 180 www.timetodare.com Section.7 Derivatives and Rates of Cange Part II Section.8 Te Derivative as a Function Derivatives ( ) In te previous section we defined te slope of te tangent to a curve wit

More information

LIMITS AND DERIVATIVES CONDITIONS FOR THE EXISTENCE OF A LIMIT

LIMITS AND DERIVATIVES CONDITIONS FOR THE EXISTENCE OF A LIMIT LIMITS AND DERIVATIVES Te limit of a function is defined as te value of y tat te curve approaces, as x approaces a particular value. Te limit of f (x) as x approaces a is written as f (x) approaces, as

More information

MAT 1339-S14 Class 2

MAT 1339-S14 Class 2 MAT 1339-S14 Class 2 July 07, 2014 Contents 1 Rate of Cange 1 1.5 Introduction to Derivatives....................... 1 2 Derivatives 5 2.1 Derivative of Polynomial function.................... 5 2.2 Te

More information

Introduction to Derivatives

Introduction to Derivatives Introduction to Derivatives 5-Minute Review: Instantaneous Rates and Tangent Slope Recall te analogy tat we developed earlier First we saw tat te secant slope of te line troug te two points (a, f (a))

More information

Function Composition and Chain Rules

Function Composition and Chain Rules Function Composition and s James K. Peterson Department of Biological Sciences and Department of Matematical Sciences Clemson University Marc 8, 2017 Outline 1 Function Composition and Continuity 2 Function

More information

Numerical Differentiation

Numerical Differentiation Numerical Differentiation Finite Difference Formulas for te first derivative (Using Taylor Expansion tecnique) (section 8.3.) Suppose tat f() = g() is a function of te variable, and tat as 0 te function

More information

MAT244 - Ordinary Di erential Equations - Summer 2016 Assignment 2 Due: July 20, 2016

MAT244 - Ordinary Di erential Equations - Summer 2016 Assignment 2 Due: July 20, 2016 MAT244 - Ordinary Di erential Equations - Summer 206 Assignment 2 Due: July 20, 206 Full Name: Student #: Last First Indicate wic Tutorial Section you attend by filling in te appropriate circle: Tut 0

More information

We name Functions f (x) or g(x) etc.

We name Functions f (x) or g(x) etc. Section 2 1B: Function Notation Bot of te equations y 2x +1 and y 3x 2 are functions. It is common to ave two or more functions in terms of x in te same problem. If I ask you wat is te value for y if x

More information

Integral Calculus, dealing with areas and volumes, and approximate areas under and between curves.

Integral Calculus, dealing with areas and volumes, and approximate areas under and between curves. Calculus can be divided into two ke areas: Differential Calculus dealing wit its, rates of cange, tangents and normals to curves, curve sketcing, and applications to maima and minima problems Integral

More information

The Schrödinger Equation and the Scale Principle

The Schrödinger Equation and the Scale Principle Te Scrödinger Equation and te Scale Princile RODOLFO A. FRINO Jul 014 Electronics Engineer Degree fro te National Universit of Mar del Plata - Argentina rodolfo_frino@aoo.co.ar Earlier tis ear (Ma) I wrote

More information

Volume 29, Issue 3. Existence of competitive equilibrium in economies with multi-member households

Volume 29, Issue 3. Existence of competitive equilibrium in economies with multi-member households Volume 29, Issue 3 Existence of competitive equilibrium in economies wit multi-member ouseolds Noriisa Sato Graduate Scool of Economics, Waseda University Abstract Tis paper focuses on te existence of

More information

1 ode.mcd. Find solution to ODE dy/dx=f(x,y). Instructor: Nam Sun Wang

1 ode.mcd. Find solution to ODE dy/dx=f(x,y). Instructor: Nam Sun Wang Fin solution to ODE /=f(). Instructor: Nam Sun Wang oe.mc Backgroun. Wen a sstem canges wit time or wit location, a set of ifferential equations tat contains erivative terms "/" escribe suc a namic sstem.

More information

5.1 The derivative or the gradient of a curve. Definition and finding the gradient from first principles

5.1 The derivative or the gradient of a curve. Definition and finding the gradient from first principles Capter 5: Dierentiation In tis capter, we will study: 51 e derivative or te gradient o a curve Deinition and inding te gradient ro irst principles 5 Forulas or derivatives 5 e equation o te tangent line

More information

Chapter 2 Limits and Continuity

Chapter 2 Limits and Continuity 4 Section. Capter Limits and Continuity Section. Rates of Cange and Limits (pp. 6) Quick Review.. f () ( ) () 4 0. f () 4( ) 4. f () sin sin 0 4. f (). 4 4 4 6. c c c 7. 8. c d d c d d c d c 9. 8 ( )(

More information

Notes on wavefunctions II: momentum wavefunctions

Notes on wavefunctions II: momentum wavefunctions Notes on wavefunctions II: momentum wavefunctions and uncertainty Te state of a particle at any time is described by a wavefunction ψ(x). Tese wavefunction must cange wit time, since we know tat particles

More information

1 The concept of limits (p.217 p.229, p.242 p.249, p.255 p.256) 1.1 Limits Consider the function determined by the formula 3. x since at this point

1 The concept of limits (p.217 p.229, p.242 p.249, p.255 p.256) 1.1 Limits Consider the function determined by the formula 3. x since at this point MA00 Capter 6 Calculus and Basic Linear Algebra I Limits, Continuity and Differentiability Te concept of its (p.7 p.9, p.4 p.49, p.55 p.56). Limits Consider te function determined by te formula f Note

More information

Practice Problem Solutions: Exam 1

Practice Problem Solutions: Exam 1 Practice Problem Solutions: Exam 1 1. (a) Algebraic Solution: Te largest term in te numerator is 3x 2, wile te largest term in te denominator is 5x 2 3x 2 + 5. Tus lim x 5x 2 2x 3x 2 x 5x 2 = 3 5 Numerical

More information

Chapter 1 Functions and Graphs. Section 1.5 = = = 4. Check Point Exercises The slope of the line y = 3x+ 1 is 3.

Chapter 1 Functions and Graphs. Section 1.5 = = = 4. Check Point Exercises The slope of the line y = 3x+ 1 is 3. Capter Functions and Graps Section. Ceck Point Exercises. Te slope of te line y x+ is. y y m( x x y ( x ( y ( x+ point-slope y x+ 6 y x+ slope-intercept. a. Write te equation in slope-intercept form: x+

More information

Statistical Treatment Choice Based on. Asymmetric Minimax Regret Criteria

Statistical Treatment Choice Based on. Asymmetric Minimax Regret Criteria Statistical Treatment Coice Based on Asymmetric Minimax Regret Criteria Aleksey Tetenov y Deartment of Economics ortwestern University ovember 5, 007 (JOB MARKET PAPER) Abstract Tis aer studies te roblem

More information

y = 3 2 x 3. The slope of this line is 3 and its y-intercept is (0, 3). For every two units to the right, the line rises three units vertically.

y = 3 2 x 3. The slope of this line is 3 and its y-intercept is (0, 3). For every two units to the right, the line rises three units vertically. Mat 2 - Calculus for Management and Social Science. Understanding te basics of lines in te -plane is crucial to te stud of calculus. Notes Recall tat te and -intercepts of a line are were te line meets

More information

Consider a function f we ll specify which assumptions we need to make about it in a minute. Let us reformulate the integral. 1 f(x) dx.

Consider a function f we ll specify which assumptions we need to make about it in a minute. Let us reformulate the integral. 1 f(x) dx. Capter 2 Integrals as sums and derivatives as differences We now switc to te simplest metods for integrating or differentiating a function from its function samples. A careful study of Taylor expansions

More information

5.1 We will begin this section with the definition of a rational expression. We

5.1 We will begin this section with the definition of a rational expression. We Basic Properties and Reducing to Lowest Terms 5.1 We will begin tis section wit te definition of a rational epression. We will ten state te two basic properties associated wit rational epressions and go

More information

Math 34A Practice Final Solutions Fall 2007

Math 34A Practice Final Solutions Fall 2007 Mat 34A Practice Final Solutions Fall 007 Problem Find te derivatives of te following functions:. f(x) = 3x + e 3x. f(x) = x + x 3. f(x) = (x + a) 4. Is te function 3t 4t t 3 increasing or decreasing wen

More information

b 1 A = bh h r V = pr

b 1 A = bh h r V = pr . Te use of a calculator is not permitted.. All variables and expressions used represent real numbers unless oterwise indicated.. Figures provided in tis test are drawn to scale unless oterwise indicated..

More information

LIMITATIONS OF EULER S METHOD FOR NUMERICAL INTEGRATION

LIMITATIONS OF EULER S METHOD FOR NUMERICAL INTEGRATION LIMITATIONS OF EULER S METHOD FOR NUMERICAL INTEGRATION LAURA EVANS.. Introduction Not all differential equations can be explicitly solved for y. Tis can be problematic if we need to know te value of y

More information

2.8 The Derivative as a Function

2.8 The Derivative as a Function .8 Te Derivative as a Function Typically, we can find te derivative of a function f at many points of its domain: Definition. Suppose tat f is a function wic is differentiable at every point of an open

More information

arxiv: v1 [math.na] 11 Apr 2016

arxiv: v1 [math.na] 11 Apr 2016 Hig order approximation to non-smoot multivariate functions Anat Amir David Levin arxiv:164.281v1 [mat.na] 11 Apr 216 April 12, 216 Abstract Approximations of non-smoot multivariate functions return low-order

More information

1.5 Functions and Their Rates of Change

1.5 Functions and Their Rates of Change 66_cpp-75.qd /6/8 4:8 PM Page 56 56 CHAPTER Introduction to Functions and Graps.5 Functions and Teir Rates of Cange Identif were a function is increasing or decreasing Use interval notation Use and interpret

More information

MATH 1A Midterm Practice September 29, 2014

MATH 1A Midterm Practice September 29, 2014 MATH A Midterm Practice September 9, 04 Name: Problem. (True/False) If a function f : R R is injective, ten f as an inverse. Solution: True. If f is injective, ten it as an inverse since tere does not

More information

MA455 Manifolds Solutions 1 May 2008

MA455 Manifolds Solutions 1 May 2008 MA455 Manifolds Solutions 1 May 2008 1. (i) Given real numbers a < b, find a diffeomorpism (a, b) R. Solution: For example first map (a, b) to (0, π/2) and ten map (0, π/2) diffeomorpically to R using

More information

International Journal of Industrial Engineering Computations

International Journal of Industrial Engineering Computations International Journal of Industrial Engineering Coutations 3 (0 695 70 Contents lists available at GrowingScience International Journal of Industrial Engineering Coutations oeage: wwwgrowingscienceco/ijiec

More information

U b (x b ) = xb 1x b 2 x a 1. means the consumption of good i by an h-type person.

U b (x b ) = xb 1x b 2 x a 1. means the consumption of good i by an h-type person. Capter 9 Welfare Eercise 9. In a two-commodity ecange economy tere are two large equalsized groups of traders. Eac trader in group a as an endowment of 300 units of commodity ; eac person in group b as

More information

Lesson 6: The Derivative

Lesson 6: The Derivative Lesson 6: Te Derivative Def. A difference quotient for a function as te form f(x + ) f(x) (x + ) x f(x + x) f(x) (x + x) x f(a + ) f(a) (a + ) a Notice tat a difference quotient always as te form of cange

More information

1 (10) 2 (10) 3 (10) 4 (10) 5 (10) 6 (10) Total (60)

1 (10) 2 (10) 3 (10) 4 (10) 5 (10) 6 (10) Total (60) First Name: OSU Number: Last Name: Signature: OKLAHOMA STATE UNIVERSITY Department of Matematics MATH 2144 (Calculus I) Instructor: Dr. Matias Sculze MIDTERM 1 September 17, 2008 Duration: 50 minutes No

More information

INTRODUCTION TO CALCULUS LIMITS

INTRODUCTION TO CALCULUS LIMITS Calculus can be divided into two ke areas: INTRODUCTION TO CALCULUS Differential Calculus dealing wit its, rates of cange, tangents and normals to curves, curve sketcing, and applications to maima and

More information

The Krewe of Caesar Problem. David Gurney. Southeastern Louisiana University. SLU 10541, 500 Western Avenue. Hammond, LA

The Krewe of Caesar Problem. David Gurney. Southeastern Louisiana University. SLU 10541, 500 Western Avenue. Hammond, LA Te Krewe of Caesar Problem David Gurney Souteastern Louisiana University SLU 10541, 500 Western Avenue Hammond, LA 7040 June 19, 00 Krewe of Caesar 1 ABSTRACT Tis paper provides an alternative to te usual

More information

Chapter 5 FINITE DIFFERENCE METHOD (FDM)

Chapter 5 FINITE DIFFERENCE METHOD (FDM) MEE7 Computer Modeling Tecniques in Engineering Capter 5 FINITE DIFFERENCE METHOD (FDM) 5. Introduction to FDM Te finite difference tecniques are based upon approximations wic permit replacing differential

More information

Derivatives of Exponentials

Derivatives of Exponentials mat 0 more on derivatives: day 0 Derivatives of Eponentials Recall tat DEFINITION... An eponential function as te form f () =a, were te base is a real number a > 0. Te domain of an eponential function

More information

UNIVERSITY OF MANITOBA DEPARTMENT OF MATHEMATICS MATH 1510 Applied Calculus I FIRST TERM EXAMINATION - Version A October 12, :30 am

UNIVERSITY OF MANITOBA DEPARTMENT OF MATHEMATICS MATH 1510 Applied Calculus I FIRST TERM EXAMINATION - Version A October 12, :30 am DEPARTMENT OF MATHEMATICS MATH 1510 Applied Calculus I October 12, 2016 8:30 am LAST NAME: FIRST NAME: STUDENT NUMBER: SIGNATURE: (I understand tat ceating is a serious offense DO NOT WRITE IN THIS TABLE

More information

A h u h = f h. 4.1 The CoarseGrid SystemandtheResidual Equation

A h u h = f h. 4.1 The CoarseGrid SystemandtheResidual Equation Capter Grid Transfer Remark. Contents of tis capter. Consider a grid wit grid size and te corresponding linear system of equations A u = f. Te summary given in Section 3. leads to te idea tat tere migt

More information

2.11 That s So Derivative

2.11 That s So Derivative 2.11 Tat s So Derivative Introduction to Differential Calculus Just as one defines instantaneous velocity in terms of average velocity, we now define te instantaneous rate of cange of a function at a point

More information