Chapter Summary. Mathematical Induction Strong Induction Recursive Definitions Structural Induction Recursive Algorithms

Size: px
Start display at page:

Download "Chapter Summary. Mathematical Induction Strong Induction Recursive Definitions Structural Induction Recursive Algorithms"

Transcription

1 Chapter 5 1

2 Chapter Summary Mathematical Inductin Strng Inductin Recursive Definitins Structural Inductin Recursive Algrithms

3 Sectin 5.1 3

4 Sectin Summary Mathematical Inductin Examples f Prf by Mathematical Inductin Guidelines fr Prfs by Mathematical Inductin

5 Climbing an Infinite Ladder Suppse we have an infinite ladder: We can reach the first rung f the ladder. If we can reach a particular rung f the ladder, then we can reach the next rung. Can we reach every step n the ladder?

6 Principle f Mathematical Inductin Principle f Mathematical Inductin: T prve that P(n) is true fr all psitive integers n, we cmplete these steps: Basis Step: Shw that P(1) is true. Inductive Step: Shw that P(k) P(k + 1) is true fr all psitive integers k. T cmplete the inductive step, assuming the inductive hypthesis that P(k) hlds fr an arbitrary integer k, shw that must P(k + 1) be true. 6

7 Principle f Mathematical Inductin Climbing an Infinite Ladder Example: BASIS STEP: By (1), we can reach rung 1. INDUCTIVE STEP: Assume the inductive hypthesis that we can reach rung k. Then by (2), we can reach rung k + 1. Hence, P(k) P(k + 1) is true fr all psitive integers k. We can reach every rung n the ladder. 7

8 Imprtant Pints Mathematical inductin can be expressed as the rule f inference (P(1) k (P(k) P(k + 1))) n P(n), where the dmain is the set f psitive integers. In a prf by mathematical inductin, we dn t assume that P(k) is true fr all psitive integers! We shw that if we assume that P(k) is true, then P(k + 1) must als be true. Prfs by mathematical inductin d nt always start at the integer 1. In such a case, the basis step begins at a starting pint b where b is an integer. Mathematical inductin is valid because f the well rdering prperty

9 Hw Mathematical Inductin Wrks Cnsider an infinite sequence f dmines, labeled 1,2,3,, where each dmin is standing. Let P(n) be the prpsitin that the n th dmin is kncked ver. knw that the first dmin is kncked dwn, i.e., P(1) is true. We als knw that if whenever the k th dmin is kncked ver, it kncks ver the (k + 1) st dmin, i.e, P(k) P(k + 1) is true fr all psitive integers k. Hence, all dmins are kncked ver. P(n) is true fr all psitive integers n.

10 Examples Example: Shw that: Slutin: BASIS STEP: P(1) is true since 1(1 + 1)/2 = 1. INDUCTIVE STEP: Assume true fr P(k). The inductive hypthesis is Under this assumptin, Hence, we have shwn that P(k + 1) fllws frm P(k). Therefre the sum f the first n psitive integers is

11 Examples Example: Use mathematical inductin t shw that fr all nnnegative integers n Slutin: P(n): fr all nnnegative integers n BASIS STEP: P(0) is true since 2 0 = 1 = This cmpletes the basis step. INDUCTIVE STEP: assume that P(k) is true fr an arbitrary nnnegative integer k k = 2 k+1 1. shw that assume that P(k) is true, then P(k + 1) is als true k + 2 k+1 = 2 (k+1)+ 1 1 = 2 k+2 1 Under the assumptin f P(k), we see that k + 2 k+1 = ( k ) + 2 k+1 =(2 k+1 1) + 2 k+1 = 2 2 k+1 1= 2 k+2 1. Because we have cmpleted the basis step and the inductive step, by mathematical inductin we knw that P(n) is true fr all nnnegative integers n. That is, n = 2 n+1 1 fr all nnnegative integers n.

12 Examples Example: Cnjecture and prve crrect a frmula fr the sum f the first n psitive dd integers. Then prve yur cnjecture. Slutin: We have: 1= 1, = 4, = 9, = 16, = 25. We can cnjecture that the sum f the first n psitive dd integers is n 2, (2n 1) + (2n + 1) =n 2.

13 Examples P(n): (2n 1) + (2n + 1) =n 2. BASIS STEP: P(1) is true since 1 2 = 1. INDUCTIVE STEP: P(k) P(k + 1) fr every psitive integer k. Assume the inductive hypthesis hlds and then shw that P(k) hlds has well. Inductive Hypthesis: (2k 1) =k 2 S, assuming P(k), it fllws that: (2k 1) + (2k + 1) =[ (2k 1)] + (2k + 1) = k 2 + (2k + 1) = k 2 + 2k + 1 = (k + 1) 2 Hence, we have shwn that P(k + 1) fllws frm P(k). Therefre the sum f the first n psitive dd integers is n 2.

14 Examples Example: Use mathematical inductin t prve that 2 n < n!, fr every integer n 4. Slutin: Let P(n) be the prpsitin that 2 n < n!. BASIS STEP: P(4) is true since 2 4 = 16 < 4! = 24. INDUCTIVE STEP: Assume P(k) hlds, i.e., 2 k integer k 4. T shw that P(k + 1) hlds: 2 k+1 = 2 2 k < 2 k! (by the inductive hypthesis) < (k + 1)k! = (k + 1)! Therefre, 2 n < n! hlds, fr every integer n 4. < k! fr an arbitrary

15 Examples Example: Use mathematical inductin t shw that if S is a finite set with n elements, where n is a nnnegative integer, then S has 2 n subsets. Slutin: P(n) be the prpsitin that a set with n elements has 2 n subsets. Basis Step: P(0) is true, because the empty set has nly itself as a subset and 2 0 = 1. Inductive Step: Assume P(k) is true fr an arbitrary nnnegative integer k. Inductive Hypthesis: Fr an arbitrary nnnegative integer k, every set with k elements has 2 k subsets. Let T be a set with k + 1 elements. Then T = S {a}, where a T and S = T {a}. Fr each subset X f S, there are exactly tw subsets f T, i.e., X and X {a}. By the inductive hypthesis S has 2 k subsets. Since there are tw subsets f T fr each subset f S, the number f subsets f T is 2 2 k = 2 k+1. Because we have cmpleted the basis step and the inductive step, by mathematical inductin if S is a finite set with n elements, where n is a nnnegative integer, then S has 2 n subsets.

16

17 Sectin 5.2

18 Sectin Summary Strng Inductin Example Prfs using Strng Inductin Well-rdering prperty

19 Strng Inductin Strng Inductin: T prve that P(n) is true fr all psitive integers n, where P(n) is a prpsitinal functin, cmplete tw steps: Basis Step: Verify that the prpsitin P(1) is true. Inductive Step: Shw the cnditinal statement [P(1) P(2) P(k)] P(k + 1) hlds fr all psitive integers k. Strng Inductin is smetimes called the secnd principle f mathematical inductin r cmplete inductin.

20 Strng Inductin and the Infinite Ladder Strng inductin tells us that we can reach all rungs if: We can reach the first rung f the ladder. Fr every integer k, if we can reach the first k rungs, then we can reach the (k + 1)st rung.

21 Examples Example: Suppse we can reach the first and secnd rungs f an infinite ladder, and we knw that if we can reach a rung, then we can reach tw rungs higher. Prve that we can reach every rung. Slutin: Prve the result using strng inductin. BASIS STEP: We can reach the first step. INDUCTIVE STEP: The inductive hypthesis is that we can reach the first k rungs, fr any k 2. We can reach the (k + 1)st rung since we can reach the (k 1)st rung by the inductive hypthesis. Hence, we can reach all rungs f the ladder.

22 Examples Example: Prve that every amunt f pstage f 12 cents r mre can be frmed using just 4-cent and 5-cent stamps. Prve the result using Mathematical inductin. BASIS STEP: Pstage f 12 cents can be frmed using three 4-cent stamps. INDUCTIVE STEP: assume P(k) is true. That is, pstage f k cents can be frmed using 4-cent and 5-cent stamps. T cmplete the inductive step, assume P(k) is true, then P(k + 1) is als true where k 12. That is, if we can frm pstage f k cents, then we can frm pstage f k + 1 cents. S, assume the inductive hypthesis is true; tw cases, when at least ne 4-cent stamp has been used and when n 4-cent stamps have been used. First, suppse that at least ne 4-cent stamp was used t frm pstage f k cents. Then we can replace this stamp with a 5-cent stamp t frm pstage f k + 1 cents. But if n 4-cent stamps were used, we can frm pstage f k cents using nly 5-cent stamps. Mrever, because k 12, we needed at least three 5-cent stamps t frm pstage f k cents. S, we can replace three 5-cent stamps with fur 4-cent stamps t frm pstage f k + 1 cents. This cmpletes the inductive step. Cnclusin

23 Examples Example: Prve that every amunt f pstage f 12 cents r mre can be frmed using just 4-cent and 5-cent stamps. Prve the result using Strng inductin. BASIS STEP: Shw that P(12), P(13), P(14), and P(15) are true. This cmpletes the basis step. INDUCTIVE STEP: The inductive hypthesis is the statement that P(j) is true fr 12 j k, where k is an integer with k 15. T cmplete the inductive step, assume that we can frm pstage f j cents, where 12 j k. Then shw that under the assumptin that P(k + 1) is true, we can als frm pstage f k + 1 cents. Using the inductive hypthesis, we can assume that P(k 3) is true because k 3 12, that is, we can frm pstage f k 3 cents using just 4-cent and 5-cent stamps. T frm pstage f k + 1 cents, we need nly add anther 4-cent stamp t the stamps we used t frm pstage f k 3 cents. That is, we have shwn that if the inductive hypthesis is true, then P(k + 1) is als true. This cmpletes the inductive step. Cnclusin

24 Well-rdering prperty The well-prperty prperty: every nnempty set f nnnegative integers has a least element. Used t prve the validity f mathematical inductin and strng inductin Mathematic inductin If P(1) is true and P(k)->P(k+1) is true, then P(n) must be true fr all integer n. Prf by cntradictin Assume at least ne psitive integer fr which P(n) is false, that is,the set S f psitive integers fr which P(n) is false is nnempty. By well-rdering prperty, S has a least element m m>1, then 0<m-1<m, hence, nt is S Then, P(m-1) must be true, then P(m-1)->P(m) is true which is a cntradictin.

25 Which Frm f Inductin Shuld Be Used? We can always use strng inductin instead f mathematical inductin. But there is n reasn t use it if it is simpler t use mathematical inductin. (See page 335 f text.) In fact, the principles f mathematical inductin, strng inductin, and the well-rdering prperty are all equivalent. (Exercises 41-43) Smetimes it is clear hw t prceed using ne f the three methds, but nt the ther tw.

Revisiting the Socrates Example

Revisiting the Socrates Example Sectin 1.6 Sectin Summary Valid Arguments Inference Rules fr Prpsitinal Lgic Using Rules f Inference t Build Arguments Rules f Inference fr Quantified Statements Building Arguments fr Quantified Statements

More information

A proposition is a statement that can be either true (T) or false (F), (but not both).

A proposition is a statement that can be either true (T) or false (F), (but not both). 400 lecture nte #1 [Ch 2, 3] Lgic and Prfs 1.1 Prpsitins (Prpsitinal Lgic) A prpsitin is a statement that can be either true (T) r false (F), (but nt bth). "The earth is flat." -- F "March has 31 days."

More information

Climbing an Infinite Ladder

Climbing an Infinite Ladder Section 5.1 Section Summary Mathematical Induction Examples of Proof by Mathematical Induction Mistaken Proofs by Mathematical Induction Guidelines for Proofs by Mathematical Induction Climbing an Infinite

More information

Homology groups of disks with holes

Homology groups of disks with holes Hmlgy grups f disks with hles THEOREM. Let p 1,, p k } be a sequence f distinct pints in the interir unit disk D n where n 2, and suppse that fr all j the sets E j Int D n are clsed, pairwise disjint subdisks.

More information

**DO NOT ONLY RELY ON THIS STUDY GUIDE!!!**

**DO NOT ONLY RELY ON THIS STUDY GUIDE!!!** Tpics lists: UV-Vis Absrbance Spectrscpy Lab & ChemActivity 3-6 (nly thrugh 4) I. UV-Vis Absrbance Spectrscpy Lab Beer s law Relates cncentratin f a chemical species in a slutin and the absrbance f that

More information

Climbing an Infinite Ladder

Climbing an Infinite Ladder Section 5.1 Section Summary Mathematical Induction Examples of Proof by Mathematical Induction Mistaken Proofs by Mathematical Induction Guidelines for Proofs by Mathematical Induction Climbing an Infinite

More information

Differentiation Applications 1: Related Rates

Differentiation Applications 1: Related Rates Differentiatin Applicatins 1: Related Rates 151 Differentiatin Applicatins 1: Related Rates Mdel 1: Sliding Ladder 10 ladder y 10 ladder 10 ladder A 10 ft ladder is leaning against a wall when the bttm

More information

Math 0310 Final Exam Review Problems

Math 0310 Final Exam Review Problems Math 0310 Final Exam Review Prblems Slve the fllwing equatins. 1. 4dd + 2 = 6 2. 2 3 h 5 = 7 3. 2 + (18 xx) + 2(xx 1) = 4(xx + 2) 8 4. 1 4 yy 3 4 = 1 2 yy + 1 5. 5.74aa + 9.28 = 2.24aa 5.42 Slve the fllwing

More information

Mathematical Induction. Section 5.1

Mathematical Induction. Section 5.1 Mathematical Induction Section 5.1 Section Summary Mathematical Induction Examples of Proof by Mathematical Induction Mistaken Proofs by Mathematical Induction Guidelines for Proofs by Mathematical Induction

More information

On Topological Structures and. Fuzzy Sets

On Topological Structures and. Fuzzy Sets L - ZHR UNIVERSIT - GZ DENSHIP OF GRDUTE STUDIES & SCIENTIFIC RESERCH On Tplgical Structures and Fuzzy Sets y Nashaat hmed Saleem Raab Supervised by Dr. Mhammed Jamal Iqelan Thesis Submitted in Partial

More information

READING STATECHART DIAGRAMS

READING STATECHART DIAGRAMS READING STATECHART DIAGRAMS Figure 4.48 A Statechart diagram with events The diagram in Figure 4.48 shws all states that the bject plane can be in during the curse f its life. Furthermre, it shws the pssible

More information

Discrete Mathematics. Spring 2017

Discrete Mathematics. Spring 2017 Discrete Mathematics Spring 2017 Previous Lecture Principle of Mathematical Induction Mathematical Induction: rule of inference Mathematical Induction: Conjecturing and Proving Climbing an Infinite Ladder

More information

With Question/Answer Animations

With Question/Answer Animations Chapter 5 With Question/Answer Animations Copyright McGraw-Hill Education. All rights reserved. No reproduction or distribution without the prior written consent of McGraw-Hill Education. Chapter Summary

More information

A new Type of Fuzzy Functions in Fuzzy Topological Spaces

A new Type of Fuzzy Functions in Fuzzy Topological Spaces IOSR Jurnal f Mathematics (IOSR-JM e-issn: 78-578, p-issn: 39-765X Vlume, Issue 5 Ver I (Sep - Oct06, PP 8-4 wwwisrjurnalsrg A new Type f Fuzzy Functins in Fuzzy Tplgical Spaces Assist Prf Dr Munir Abdul

More information

CHAPTER 24: INFERENCE IN REGRESSION. Chapter 24: Make inferences about the population from which the sample data came.

CHAPTER 24: INFERENCE IN REGRESSION. Chapter 24: Make inferences about the population from which the sample data came. MATH 1342 Ch. 24 April 25 and 27, 2013 Page 1 f 5 CHAPTER 24: INFERENCE IN REGRESSION Chapters 4 and 5: Relatinships between tw quantitative variables. Be able t Make a graph (scatterplt) Summarize the

More information

Admissibility Conditions and Asymptotic Behavior of Strongly Regular Graphs

Admissibility Conditions and Asymptotic Behavior of Strongly Regular Graphs Admissibility Cnditins and Asympttic Behavir f Strngly Regular Graphs VASCO MOÇO MANO Department f Mathematics University f Prt Oprt PORTUGAL vascmcman@gmailcm LUÍS ANTÓNIO DE ALMEIDA VIEIRA Department

More information

Equilibrium of Stress

Equilibrium of Stress Equilibrium f Stress Cnsider tw perpendicular planes passing thrugh a pint p. The stress cmpnents acting n these planes are as shwn in ig. 3.4.1a. These stresses are usuall shwn tgether acting n a small

More information

Trigonometric Ratios Unit 5 Tentative TEST date

Trigonometric Ratios Unit 5 Tentative TEST date 1 U n i t 5 11U Date: Name: Trignmetric Ratis Unit 5 Tentative TEST date Big idea/learning Gals In this unit yu will extend yur knwledge f SOH CAH TOA t wrk with btuse and reflex angles. This extensin

More information

Name: Period: Date: BONDING NOTES ADVANCED CHEMISTRY

Name: Period: Date: BONDING NOTES ADVANCED CHEMISTRY Name: Perid: Date: BONDING NOTES ADVANCED CHEMISTRY Directins: This packet will serve as yur ntes fr this chapter. Fllw alng with the PwerPint presentatin and fill in the missing infrmatin. Imprtant terms

More information

Dataflow Analysis and Abstract Interpretation

Dataflow Analysis and Abstract Interpretation Dataflw Analysis and Abstract Interpretatin Cmputer Science and Artificial Intelligence Labratry MIT Nvember 9, 2015 Recap Last time we develped frm first principles an algrithm t derive invariants. Key

More information

AP Statistics Practice Test Unit Three Exploring Relationships Between Variables. Name Period Date

AP Statistics Practice Test Unit Three Exploring Relationships Between Variables. Name Period Date AP Statistics Practice Test Unit Three Explring Relatinships Between Variables Name Perid Date True r False: 1. Crrelatin and regressin require explanatry and respnse variables. 1. 2. Every least squares

More information

Review Problems 3. Four FIR Filter Types

Review Problems 3. Four FIR Filter Types Review Prblems 3 Fur FIR Filter Types Fur types f FIR linear phase digital filters have cefficients h(n fr 0 n M. They are defined as fllws: Type I: h(n = h(m-n and M even. Type II: h(n = h(m-n and M dd.

More information

E Z, (n l. and, if in addition, for each integer n E Z there is a unique factorization of the form

E Z, (n l. and, if in addition, for each integer n E Z there is a unique factorization of the form Revista Clmbiana de Matematias Vlumen II,1968,pags.6-11 A NOTE ON GENERALIZED MOBIUS f-functions V.S. by ALBIS In [1] the ncept f a cnjugate pair f sets f psi tive integers is int~dued Briefly, if Z dentes

More information

CHAPTER 3 INEQUALITIES. Copyright -The Institute of Chartered Accountants of India

CHAPTER 3 INEQUALITIES. Copyright -The Institute of Chartered Accountants of India CHAPTER 3 INEQUALITIES Cpyright -The Institute f Chartered Accuntants f India INEQUALITIES LEARNING OBJECTIVES One f the widely used decisin making prblems, nwadays, is t decide n the ptimal mix f scarce

More information

Induction and recursion. Chapter 5

Induction and recursion. Chapter 5 Induction and recursion Chapter 5 Chapter Summary Mathematical Induction Strong Induction Well-Ordering Recursive Definitions Structural Induction Recursive Algorithms Mathematical Induction Section 5.1

More information

MODULE 1. e x + c. [You can t separate a demominator, but you can divide a single denominator into each numerator term] a + b a(a + b)+1 = a + b

MODULE 1. e x + c. [You can t separate a demominator, but you can divide a single denominator into each numerator term] a + b a(a + b)+1 = a + b . REVIEW OF SOME BASIC ALGEBRA MODULE () Slving Equatins Yu shuld be able t slve fr x: a + b = c a d + e x + c and get x = e(ba +) b(c a) d(ba +) c Cmmn mistakes and strategies:. a b + c a b + a c, but

More information

Chapter Summary. Mathematical Induction Strong Induction Well-Ordering Recursive Definitions Structural Induction Recursive Algorithms

Chapter Summary. Mathematical Induction Strong Induction Well-Ordering Recursive Definitions Structural Induction Recursive Algorithms 1 Chapter Summary Mathematical Induction Strong Induction Well-Ordering Recursive Definitions Structural Induction Recursive Algorithms 2 Section 5.1 3 Section Summary Mathematical Induction Examples of

More information

Higher. Specimen NAB Assessment

Higher. Specimen NAB Assessment hsn.uk.net Higher Mathematics UNIT Specimen NAB Assessment HSN50 This dcument was prduced speciall fr the HSN.uk.net website, and we require that an cpies r derivative wrks attribute the wrk t Higher Still

More information

Induction and Recursion

Induction and Recursion . All rights reserved. Authorized only for instructor use in the classroom. No reproduction or further distribution permitted without the prior written consent of McGraw-Hill Education. Induction and Recursion

More information

x x

x x Mdeling the Dynamics f Life: Calculus and Prbability fr Life Scientists Frederick R. Adler cfrederick R. Adler, Department f Mathematics and Department f Bilgy, University f Utah, Salt Lake City, Utah

More information

The Law of Total Probability, Bayes Rule, and Random Variables (Oh My!)

The Law of Total Probability, Bayes Rule, and Random Variables (Oh My!) The Law f Ttal Prbability, Bayes Rule, and Randm Variables (Oh My!) Administrivia Hmewrk 2 is psted and is due tw Friday s frm nw If yu didn t start early last time, please d s this time. Gd Milestnes:

More information

Sections 15.1 to 15.12, 16.1 and 16.2 of the textbook (Robbins-Miller) cover the materials required for this topic.

Sections 15.1 to 15.12, 16.1 and 16.2 of the textbook (Robbins-Miller) cover the materials required for this topic. Tpic : AC Fundamentals, Sinusidal Wavefrm, and Phasrs Sectins 5. t 5., 6. and 6. f the textbk (Rbbins-Miller) cver the materials required fr this tpic.. Wavefrms in electrical systems are current r vltage

More information

CS 477/677 Analysis of Algorithms Fall 2007 Dr. George Bebis Course Project Due Date: 11/29/2007

CS 477/677 Analysis of Algorithms Fall 2007 Dr. George Bebis Course Project Due Date: 11/29/2007 CS 477/677 Analysis f Algrithms Fall 2007 Dr. Gerge Bebis Curse Prject Due Date: 11/29/2007 Part1: Cmparisn f Srting Algrithms (70% f the prject grade) The bjective f the first part f the assignment is

More information

A New Evaluation Measure. J. Joiner and L. Werner. The problems of evaluation and the needed criteria of evaluation

A New Evaluation Measure. J. Joiner and L. Werner. The problems of evaluation and the needed criteria of evaluation III-l III. A New Evaluatin Measure J. Jiner and L. Werner Abstract The prblems f evaluatin and the needed criteria f evaluatin measures in the SMART system f infrmatin retrieval are reviewed and discussed.

More information

Computational modeling techniques

Computational modeling techniques Cmputatinal mdeling techniques Lecture 2: Mdeling change. In Petre Department f IT, Åb Akademi http://users.ab.fi/ipetre/cmpmd/ Cntent f the lecture Basic paradigm f mdeling change Examples Linear dynamical

More information

1. What is the difference between complementary and supplementary angles?

1. What is the difference between complementary and supplementary angles? Name 1 Date Angles Intrductin t Angles Part 1 Independent Practice 1. What is the difference between cmplementary and supplementary angles? 2. Suppse m TOK = 49. Part A: What is the measure f the angle

More information

Fall 2013 Physics 172 Recitation 3 Momentum and Springs

Fall 2013 Physics 172 Recitation 3 Momentum and Springs Fall 03 Physics 7 Recitatin 3 Mmentum and Springs Purpse: The purpse f this recitatin is t give yu experience wrking with mmentum and the mmentum update frmula. Readings: Chapter.3-.5 Learning Objectives:.3.

More information

MATHEMATICS Higher Grade - Paper I

MATHEMATICS Higher Grade - Paper I Higher Mathematics - Practice Eaminatin B Please nte the frmat f this practice eaminatin is different frm the current frmat. The paper timings are different and calculatrs can be used thrughut. MATHEMATICS

More information

Math 105: Review for Exam I - Solutions

Math 105: Review for Exam I - Solutions 1. Let f(x) = 3 + x + 5. Math 105: Review fr Exam I - Slutins (a) What is the natural dmain f f? [ 5, ), which means all reals greater than r equal t 5 (b) What is the range f f? [3, ), which means all

More information

SOLUTIONS TO EXERCISES FOR. MATHEMATICS 205A Part 4. Function spaces

SOLUTIONS TO EXERCISES FOR. MATHEMATICS 205A Part 4. Function spaces SOLUTIONS TO EXERCISES FOR MATHEMATICS 205A Part 4 Fall 2014 IV. Functin spaces IV.1 : General prperties Additinal exercises 1. The mapping q is 1 1 because q(f) = q(g) implies that fr all x we have f(x)

More information

Pipetting 101 Developed by BSU CityLab

Pipetting 101 Developed by BSU CityLab Discver the Micrbes Within: The Wlbachia Prject Pipetting 101 Develped by BSU CityLab Clr Cmparisns Pipetting Exercise #1 STUDENT OBJECTIVES Students will be able t: Chse the crrect size micrpipette fr

More information

NUMBERS, MATHEMATICS AND EQUATIONS

NUMBERS, MATHEMATICS AND EQUATIONS AUSTRALIAN CURRICULUM PHYSICS GETTING STARTED WITH PHYSICS NUMBERS, MATHEMATICS AND EQUATIONS An integral part t the understanding f ur physical wrld is the use f mathematical mdels which can be used t

More information

Lim f (x) e. Find the largest possible domain and its discontinuity points. Why is it discontinuous at those points (if any)?

Lim f (x) e. Find the largest possible domain and its discontinuity points. Why is it discontinuous at those points (if any)? THESE ARE SAMPLE QUESTIONS FOR EACH OF THE STUDENT LEARNING OUTCOMES (SLO) SET FOR THIS COURSE. SLO 1: Understand and use the cncept f the limit f a functin i. Use prperties f limits and ther techniques,

More information

Name: Period: Date: BONDING NOTES HONORS CHEMISTRY

Name: Period: Date: BONDING NOTES HONORS CHEMISTRY Name: Perid: Date: BONDING NOTES HONORS CHEMISTRY Directins: This packet will serve as yur ntes fr this chapter. Fllw alng with the PwerPint presentatin and fill in the missing infrmatin. Imprtant terms

More information

Lab 1 The Scientific Method

Lab 1 The Scientific Method INTRODUCTION The fllwing labratry exercise is designed t give yu, the student, an pprtunity t explre unknwn systems, r universes, and hypthesize pssible rules which may gvern the behavir within them. Scientific

More information

Math Foundations 20 Work Plan

Math Foundations 20 Work Plan Math Fundatins 20 Wrk Plan Units / Tpics 20.8 Demnstrate understanding f systems f linear inequalities in tw variables. Time Frame December 1-3 weeks 6-10 Majr Learning Indicatrs Identify situatins relevant

More information

A Simple Set of Test Matrices for Eigenvalue Programs*

A Simple Set of Test Matrices for Eigenvalue Programs* Simple Set f Test Matrices fr Eigenvalue Prgrams* By C. W. Gear** bstract. Sets f simple matrices f rder N are given, tgether with all f their eigenvalues and right eigenvectrs, and simple rules fr generating

More information

Physics 2B Chapter 23 Notes - Faraday s Law & Inductors Spring 2018

Physics 2B Chapter 23 Notes - Faraday s Law & Inductors Spring 2018 Michael Faraday lived in the Lndn area frm 1791 t 1867. He was 29 years ld when Hand Oersted, in 1820, accidentally discvered that electric current creates magnetic field. Thrugh empirical bservatin and

More information

xfyy.sny E gyef Lars g 8 2 s Zs yr Yao x ao X Axe B X'lo AtB tair z2schhyescosh's 2C scoshyesukh 8 gosh E si Eire 3AtB o X g o I

xfyy.sny E gyef Lars g 8 2 s Zs yr Yao x ao X Axe B X'lo AtB tair z2schhyescosh's 2C scoshyesukh 8 gosh E si Eire 3AtB o X g o I Math 418, Fall 2018, Midterm Prf. Sherman Name nstructins: This is a 50 minute exam. Fr credit yu must shw all relevant wrk n each prblem. Yu may nt use any calculatrs, phnes, bks, ntes, etc. There are

More information

Section 5.8 Notes Page Exponential Growth and Decay Models; Newton s Law

Section 5.8 Notes Page Exponential Growth and Decay Models; Newton s Law Sectin 5.8 Ntes Page 1 5.8 Expnential Grwth and Decay Mdels; Newtn s Law There are many applicatins t expnential functins that we will fcus n in this sectin. First let s lk at the expnential mdel. Expnential

More information

Department of Economics, University of California, Davis Ecn 200C Micro Theory Professor Giacomo Bonanno. Insurance Markets

Department of Economics, University of California, Davis Ecn 200C Micro Theory Professor Giacomo Bonanno. Insurance Markets Department f Ecnmics, University f alifrnia, Davis Ecn 200 Micr Thery Prfessr Giacm Bnann Insurance Markets nsider an individual wh has an initial wealth f. ith sme prbability p he faces a lss f x (0

More information

SOLUTIONS TO EXERCISES FOR. MATHEMATICS 205A Part 4. Function spaces

SOLUTIONS TO EXERCISES FOR. MATHEMATICS 205A Part 4. Function spaces SOLUTIONS TO EXERCISES FOR MATHEMATICS 205A Part 4 Fall 2008 IV. Functin spaces IV.1 : General prperties (Munkres, 45 47) Additinal exercises 1. Suppse that X and Y are metric spaces such that X is cmpact.

More information

Corrections for the textbook answers: Sec 6.1 #8h)covert angle to a positive by adding period #9b) # rad/sec

Corrections for the textbook answers: Sec 6.1 #8h)covert angle to a positive by adding period #9b) # rad/sec U n i t 6 AdvF Date: Name: Trignmetric Functins Unit 6 Tentative TEST date Big idea/learning Gals In this unit yu will study trignmetric functins frm grade, hwever everything will be dne in radian measure.

More information

Thermodynamics Partial Outline of Topics

Thermodynamics Partial Outline of Topics Thermdynamics Partial Outline f Tpics I. The secnd law f thermdynamics addresses the issue f spntaneity and invlves a functin called entrpy (S): If a prcess is spntaneus, then Suniverse > 0 (2 nd Law!)

More information

M thematics. National 5 Practice Paper C. Paper 1. Duration 1 hour. Total marks 40

M thematics. National 5 Practice Paper C. Paper 1. Duration 1 hour. Total marks 40 N5 M thematics Natinal 5 Practice Paper C Paper 1 Duratin 1 hur Ttal marks 40 Yu may NOT use a calculatr Attempt all the questins. Use blue r black ink. Full credit will nly be given t slutins which cntain

More information

Chapter 2 GAUSS LAW Recommended Problems:

Chapter 2 GAUSS LAW Recommended Problems: Chapter GAUSS LAW Recmmended Prblems: 1,4,5,6,7,9,11,13,15,18,19,1,7,9,31,35,37,39,41,43,45,47,49,51,55,57,61,6,69. LCTRIC FLUX lectric flux is a measure f the number f electric filed lines penetrating

More information

Compressibility Effects

Compressibility Effects Definitin f Cmpressibility All real substances are cmpressible t sme greater r lesser extent; that is, when yu squeeze r press n them, their density will change The amunt by which a substance can be cmpressed

More information

Lyapunov Stability Stability of Equilibrium Points

Lyapunov Stability Stability of Equilibrium Points Lyapunv Stability Stability f Equilibrium Pints 1. Stability f Equilibrium Pints - Definitins In this sectin we cnsider n-th rder nnlinear time varying cntinuus time (C) systems f the frm x = f ( t, x),

More information

Finite Automata. Human-aware Robo.cs. 2017/08/22 Chapter 1.1 in Sipser

Finite Automata. Human-aware Robo.cs. 2017/08/22 Chapter 1.1 in Sipser Finite Autmata 2017/08/22 Chapter 1.1 in Sipser 1 Last time Thery f cmputatin Autmata Thery Cmputability Thery Cmplexity Thery Finite autmata Pushdwn autmata Turing machines 2 Outline fr tday Finite autmata

More information

EEO 401 Digital Signal Processing Prof. Mark Fowler

EEO 401 Digital Signal Processing Prof. Mark Fowler EEO 401 Digital Signal Prcessing Prf. Mark Fwler Intrductin Nte Set #1 ading Assignment: Ch. 1 f Prakis & Manlakis 1/13 Mdern systems generally DSP Scenari get a cntinuus-time signal frm a sensr a cnt.-time

More information

5.1 Properties of Inverse Trigonometric Functions.

5.1 Properties of Inverse Trigonometric Functions. Inverse Trignmetricl Functins The inverse f functin f( ) f ( ) f : A B eists if f is ne-ne nt ie, ijectin nd is given Cnsider the e functin with dmin R nd rnge [, ] Clerl this functin is nt ijectin nd

More information

SUPPLEMENTARY MATERIAL GaGa: a simple and flexible hierarchical model for microarray data analysis

SUPPLEMENTARY MATERIAL GaGa: a simple and flexible hierarchical model for microarray data analysis SUPPLEMENTARY MATERIAL GaGa: a simple and flexible hierarchical mdel fr micrarray data analysis David Rssell Department f Bistatistics M.D. Andersn Cancer Center, Hustn, TX 77030, USA rsselldavid@gmail.cm

More information

Figure 1a. A planar mechanism.

Figure 1a. A planar mechanism. ME 5 - Machine Design I Fall Semester 0 Name f Student Lab Sectin Number EXAM. OPEN BOOK AND CLOSED NOTES. Mnday, September rd, 0 Write n ne side nly f the paper prvided fr yur slutins. Where necessary,

More information

[COLLEGE ALGEBRA EXAM I REVIEW TOPICS] ( u s e t h i s t o m a k e s u r e y o u a r e r e a d y )

[COLLEGE ALGEBRA EXAM I REVIEW TOPICS] ( u s e t h i s t o m a k e s u r e y o u a r e r e a d y ) (Abut the final) [COLLEGE ALGEBRA EXAM I REVIEW TOPICS] ( u s e t h i s t m a k e s u r e y u a r e r e a d y ) The department writes the final exam s I dn't really knw what's n it and I can't very well

More information

AP Statistics Notes Unit Two: The Normal Distributions

AP Statistics Notes Unit Two: The Normal Distributions AP Statistics Ntes Unit Tw: The Nrmal Distributins Syllabus Objectives: 1.5 The student will summarize distributins f data measuring the psitin using quartiles, percentiles, and standardized scres (z-scres).

More information

1 The limitations of Hartree Fock approximation

1 The limitations of Hartree Fock approximation Chapter: Pst-Hartree Fck Methds - I The limitatins f Hartree Fck apprximatin The n electrn single determinant Hartree Fck wave functin is the variatinal best amng all pssible n electrn single determinants

More information

Discrete Mathematics. Spring 2017

Discrete Mathematics. Spring 2017 Discrete Mathematics Spring 2017 Previous Lecture Principle of Mathematical Induction Mathematical Induction: Rule of Inference Mathematical Induction: Conjecturing and Proving Mathematical Induction:

More information

Medium Scale Integrated (MSI) devices [Sections 2.9 and 2.10]

Medium Scale Integrated (MSI) devices [Sections 2.9 and 2.10] EECS 270, Winter 2017, Lecture 3 Page 1 f 6 Medium Scale Integrated (MSI) devices [Sectins 2.9 and 2.10] As we ve seen, it s smetimes nt reasnable t d all the design wrk at the gate-level smetimes we just

More information

How do scientists measure trees? What is DBH?

How do scientists measure trees? What is DBH? Hw d scientists measure trees? What is DBH? Purpse Students develp an understanding f tree size and hw scientists measure trees. Students bserve and measure tree ckies and explre the relatinship between

More information

Internal vs. external validity. External validity. This section is based on Stock and Watson s Chapter 9.

Internal vs. external validity. External validity. This section is based on Stock and Watson s Chapter 9. Sectin 7 Mdel Assessment This sectin is based n Stck and Watsn s Chapter 9. Internal vs. external validity Internal validity refers t whether the analysis is valid fr the ppulatin and sample being studied.

More information

Concept Category 2. Trigonometry & The Unit Circle

Concept Category 2. Trigonometry & The Unit Circle Cncept Categry 2 Trignmetry & The Unit Circle Skill Checklist Use special right triangles t express values f fr the six trig functins Evaluate sine csine and tangent using the unit circle Slve tw-step

More information

ANSWER KEY FOR MATH 10 SAMPLE EXAMINATION. Instructions: If asked to label the axes please use real world (contextual) labels

ANSWER KEY FOR MATH 10 SAMPLE EXAMINATION. Instructions: If asked to label the axes please use real world (contextual) labels ANSWER KEY FOR MATH 10 SAMPLE EXAMINATION Instructins: If asked t label the axes please use real wrld (cntextual) labels Multiple Chice Answers: 0 questins x 1.5 = 30 Pints ttal Questin Answer Number 1

More information

Departamento de Economfa de la Empresa Business Economics Series 06

Departamento de Economfa de la Empresa Business Economics Series 06 ------_.. Wrking Paper 94-42 Departament de Ecnmfa de la Empresa Business Ecnmics Series 06 Universidad Carls III de Madrid Nvember 994 Calle Madrid, 26 28903 Getafe (Spain) Fax (34) 624-9875 WHEN CAN

More information

We can see from the graph above that the intersection is, i.e., [ ).

We can see from the graph above that the intersection is, i.e., [ ). MTH 111 Cllege Algebra Lecture Ntes July 2, 2014 Functin Arithmetic: With nt t much difficulty, we ntice that inputs f functins are numbers, and utputs f functins are numbers. S whatever we can d with

More information

Administrativia. Assignment 1 due thursday 9/23/2004 BEFORE midnight. Midterm exam 10/07/2003 in class. CS 460, Sessions 8-9 1

Administrativia. Assignment 1 due thursday 9/23/2004 BEFORE midnight. Midterm exam 10/07/2003 in class. CS 460, Sessions 8-9 1 Administrativia Assignment 1 due thursday 9/23/2004 BEFORE midnight Midterm eam 10/07/2003 in class CS 460, Sessins 8-9 1 Last time: search strategies Uninfrmed: Use nly infrmatin available in the prblem

More information

If (IV) is (increased, decreased, changed), then (DV) will (increase, decrease, change) because (reason based on prior research).

If (IV) is (increased, decreased, changed), then (DV) will (increase, decrease, change) because (reason based on prior research). Science Fair Prject Set Up Instructins 1) Hypthesis Statement 2) Materials List 3) Prcedures 4) Safety Instructins 5) Data Table 1) Hw t write a HYPOTHESIS STATEMENT Use the fllwing frmat: If (IV) is (increased,

More information

LEARNING : At the end of the lesson, students should be able to: OUTCOMES a) state trigonometric ratios of sin,cos, tan, cosec, sec and cot

LEARNING : At the end of the lesson, students should be able to: OUTCOMES a) state trigonometric ratios of sin,cos, tan, cosec, sec and cot Mathematics DM 05 Tpic : Trignmetric Functins LECTURE OF 5 TOPIC :.0 TRIGONOMETRIC FUNCTIONS SUBTOPIC :. Trignmetric Ratis and Identities LEARNING : At the end f the lessn, students shuld be able t: OUTCOMES

More information

WYSE Academic Challenge Regional Mathematics 2007 Solution Set

WYSE Academic Challenge Regional Mathematics 2007 Solution Set WYSE Academic Challenge Reginal Mathematics 007 Slutin Set 1. Crrect answer: C. ( ) ( ) 1 + y y = ( + ) + ( y y + 1 ) = + 1 1 ( ) ( 1 + y ) = s *1/ = 1. Crrect answer: A. The determinant is ( 1 ( 1) )

More information

Lab #3: Pendulum Period and Proportionalities

Lab #3: Pendulum Period and Proportionalities Physics 144 Chwdary Hw Things Wrk Spring 2006 Name: Partners Name(s): Intrductin Lab #3: Pendulum Perid and Prprtinalities Smetimes, it is useful t knw the dependence f ne quantity n anther, like hw the

More information

Getting Involved O. Responsibilities of a Member. People Are Depending On You. Participation Is Important. Think It Through

Getting Involved O. Responsibilities of a Member. People Are Depending On You. Participation Is Important. Think It Through f Getting Invlved O Literature Circles can be fun. It is exciting t be part f a grup that shares smething. S get invlved, read, think, and talk abut bks! Respnsibilities f a Member Remember a Literature

More information

Building to Transformations on Coordinate Axis Grade 5: Geometry Graph points on the coordinate plane to solve real-world and mathematical problems.

Building to Transformations on Coordinate Axis Grade 5: Geometry Graph points on the coordinate plane to solve real-world and mathematical problems. Building t Transfrmatins n Crdinate Axis Grade 5: Gemetry Graph pints n the crdinate plane t slve real-wrld and mathematical prblems. 5.G.1. Use a pair f perpendicular number lines, called axes, t define

More information

Precalculus A. Semester Exam Review

Precalculus A. Semester Exam Review Precalculus A 015-016 MCPS 015 016 1 The semester A eaminatin fr Precalculus cnsists f tw parts. Part 1 is selected respnse n which a calculatr will NOT be allwed. Part is shrt answer n which a calculatr

More information

1996 Engineering Systems Design and Analysis Conference, Montpellier, France, July 1-4, 1996, Vol. 7, pp

1996 Engineering Systems Design and Analysis Conference, Montpellier, France, July 1-4, 1996, Vol. 7, pp THE POWER AND LIMIT OF NEURAL NETWORKS T. Y. Lin Department f Mathematics and Cmputer Science San Jse State University San Jse, Califrnia 959-003 tylin@cs.ssu.edu and Bereley Initiative in Sft Cmputing*

More information

Bootstrap Method > # Purpose: understand how bootstrap method works > obs=c(11.96, 5.03, 67.40, 16.07, 31.50, 7.73, 11.10, 22.38) > n=length(obs) >

Bootstrap Method > # Purpose: understand how bootstrap method works > obs=c(11.96, 5.03, 67.40, 16.07, 31.50, 7.73, 11.10, 22.38) > n=length(obs) > Btstrap Methd > # Purpse: understand hw btstrap methd wrks > bs=c(11.96, 5.03, 67.40, 16.07, 31.50, 7.73, 11.10, 22.38) > n=length(bs) > mean(bs) [1] 21.64625 > # estimate f lambda > lambda = 1/mean(bs);

More information

PHOTOSYNTHESIS THE PRACTICALS 16 APRIL 2014

PHOTOSYNTHESIS THE PRACTICALS 16 APRIL 2014 PHOTOSYNTHESIS THE PRACTICALS 16 APRIL 2014 Lessn Descriptin In this lessn, we will: Review the prcess f phtsynthesis Study the starch test in leaves Study the varius practicals testing phtsynthesis Lk

More information

Five Whys How To Do It Better

Five Whys How To Do It Better Five Whys Definitin. As explained in the previus article, we define rt cause as simply the uncvering f hw the current prblem came int being. Fr a simple causal chain, it is the entire chain. Fr a cmplex

More information

Tree Structured Classifier

Tree Structured Classifier Tree Structured Classifier Reference: Classificatin and Regressin Trees by L. Breiman, J. H. Friedman, R. A. Olshen, and C. J. Stne, Chapman & Hall, 98. A Medical Eample (CART): Predict high risk patients

More information

SPH3U1 Lesson 06 Kinematics

SPH3U1 Lesson 06 Kinematics PROJECTILE MOTION LEARNING GOALS Students will: Describe the mtin f an bject thrwn at arbitrary angles thrugh the air. Describe the hrizntal and vertical mtins f a prjectile. Slve prjectile mtin prblems.

More information

Pre-Calculus Individual Test 2017 February Regional

Pre-Calculus Individual Test 2017 February Regional The abbreviatin NOTA means Nne f the Abve answers and shuld be chsen if chices A, B, C and D are nt crrect. N calculatr is allwed n this test. Arcfunctins (such as y = Arcsin( ) ) have traditinal restricted

More information

Graduate AI Lecture 16: Planning 2. Teachers: Martial Hebert Ariel Procaccia (this time)

Graduate AI Lecture 16: Planning 2. Teachers: Martial Hebert Ariel Procaccia (this time) Graduate AI Lecture 16: Planning 2 Teachers: Martial Hebert Ariel Prcaccia (this time) Reminder State is a cnjunctin f cnditins, e.g., at(truck 1,Shadyside) at(truck 2,Oakland) States are transfrmed via

More information

The Equation αsin x+ βcos family of Heron Cyclic Quadrilaterals

The Equation αsin x+ βcos family of Heron Cyclic Quadrilaterals The Equatin sin x+ βcs x= γ and a family f Hern Cyclic Quadrilaterals Knstantine Zelatr Department Of Mathematics Cllege Of Arts And Sciences Mail Stp 94 University Of Tled Tled,OH 43606-3390 U.S.A. Intrductin

More information

MATHEMATICS SYLLABUS SECONDARY 5th YEAR

MATHEMATICS SYLLABUS SECONDARY 5th YEAR Eurpean Schls Office f the Secretary-General Pedaggical Develpment Unit Ref. : 011-01-D-8-en- Orig. : EN MATHEMATICS SYLLABUS SECONDARY 5th YEAR 6 perid/week curse APPROVED BY THE JOINT TEACHING COMMITTEE

More information

CONSTRUCTING STATECHART DIAGRAMS

CONSTRUCTING STATECHART DIAGRAMS CONSTRUCTING STATECHART DIAGRAMS The fllwing checklist shws the necessary steps fr cnstructing the statechart diagrams f a class. Subsequently, we will explain the individual steps further. Checklist 4.6

More information

LHS Mathematics Department Honors Pre-Calculus Final Exam 2002 Answers

LHS Mathematics Department Honors Pre-Calculus Final Exam 2002 Answers LHS Mathematics Department Hnrs Pre-alculus Final Eam nswers Part Shrt Prblems The table at the right gives the ppulatin f Massachusetts ver the past several decades Using an epnential mdel, predict the

More information

Curriculum Development Overview Unit Planning for 8 th Grade Mathematics MA10-GR.8-S.1-GLE.1 MA10-GR.8-S.4-GLE.2

Curriculum Development Overview Unit Planning for 8 th Grade Mathematics MA10-GR.8-S.1-GLE.1 MA10-GR.8-S.4-GLE.2 Unit Title It s All Greek t Me Length f Unit 5 weeks Fcusing Lens(es) Cnnectins Standards and Grade Level Expectatins Addressed in this Unit MA10-GR.8-S.1-GLE.1 MA10-GR.8-S.4-GLE.2 Inquiry Questins (Engaging-

More information

, which yields. where z1. and z2

, which yields. where z1. and z2 The Gaussian r Nrmal PDF, Page 1 The Gaussian r Nrmal Prbability Density Functin Authr: Jhn M Cimbala, Penn State University Latest revisin: 11 September 13 The Gaussian r Nrmal Prbability Density Functin

More information

A Transition to Advanced Mathematics. Mathematics and Computer Sciences Department. o Work Experience, General. o Open Entry/Exit

A Transition to Advanced Mathematics. Mathematics and Computer Sciences Department. o Work Experience, General. o Open Entry/Exit SECTION A - Curse Infrmatin 1. Curse ID: 2. Curse Title: 3. Divisin: 4. Department: MATH 245 A Transitin t Advanced Mathematics Natural Sciences Divisin Mathematics and Cmputer Sciences Department 5. Subject:

More information

4F-5 : Performance of an Ideal Gas Cycle 10 pts

4F-5 : Performance of an Ideal Gas Cycle 10 pts 4F-5 : Perfrmance f an Cycle 0 pts An ideal gas, initially at 0 C and 00 kpa, underges an internally reversible, cyclic prcess in a clsed system. The gas is first cmpressed adiabatically t 500 kpa, then

More information

Chapter 9 Vector Differential Calculus, Grad, Div, Curl

Chapter 9 Vector Differential Calculus, Grad, Div, Curl Chapter 9 Vectr Differential Calculus, Grad, Div, Curl 9.1 Vectrs in 2-Space and 3-Space 9.2 Inner Prduct (Dt Prduct) 9.3 Vectr Prduct (Crss Prduct, Outer Prduct) 9.4 Vectr and Scalar Functins and Fields

More information

Cop yri ht 2006, Barr Mabillard.

Cop yri ht 2006, Barr Mabillard. Trignmetry II Cpyright Trignmetry II Standards 006, Test Barry ANSWERS Mabillard. 0 www.math0s.cm . If csα, where sinα > 0, and 5 cs α + β value f sin β, where tan β > 0, determine the exact 9 First determine

More information