Using Counting Techniques to Determine Probabilities

Size: px
Start display at page:

Download "Using Counting Techniques to Determine Probabilities"

Transcription

1 Kowledge ticle: obability ad Statistics Usig outig Techiques to Detemie obabilities Tee Diagams ad the Fudametal outig iciple impotat aspect of pobability theoy is the ability to detemie the total umbe of possible outcomes whe multiple evets ae cosideed. I this lesso, we ae tyig to develop coutig techiques we ca use to help compute pobabilities. Oe of the most fudametal coutig techiques is the fudametal coutig piciple (sometimes efeed to as the multiplicatio axiom). efoe we itoduce the fudametal coutig piciple, let s look at some examples. Example If a woma has two blouses {, } ad thee skits {s, s, s }, how may diffeet outfits cosistig of a blouse ad a skit ca she wea? We ca use a tee diagam to detemie the umbe of diffeet outfits. s s s s s s s s s s s s Notice we ed up with two sets (o goups) of thee outfits (thee with the fist blouse ad thee with the secod blouse). We ca also use the multiplicatio fact to detemie the umbe of outfits because the meaig of is two goups of thee. The pocedue we just employed is called the fudametal coutig piciple. The fudametal coutig piciple states that if oe task ca be doe i m ways, ad a secod task ca be doe i ways, the the opeatio ivolvig the fist task

2 followed by the secod ca be pefomed i m ways. The fudametal coutig piciple is ot limited to just two tasks; it ca be used fo ay umbe of tasks. Example tuck licese plate cosists of a lette followed by fou digits. How may such licese plates ae possible? Sice thee ae 6 possibilities fo the lette ad 0 possibilities fo each of the fou digits, the fudametal coutig piciple gives us = 60,000 possible licese plates. Detemiig obability with the Fudametal outig iciple Example tuck licese plate cosists of a lette followed by fou digits. If you select oe licese plate at adom, what is the pobability it cotais the lette Z? Recall that the defiitio of pobability is. I example, we detemied that thee ae 60,000 possible outcomes. Now, the umbe of acceptable outcomes is detemied by the fudametal coutig piciple as = 0,000. (Note thee is oly oe choice fo the lette, that beig Z.) 0,000 So, (licese plate cotais Z) =. 60,000 6

3 emutatios Suppose we ae asked to fid the sequeces that ca be fomed with the lettes {,, } if o lette is epeated. Fist let s use a tee diagam to detemie the umbe of sequeces: The tee diagam gives us six aagemets. We ca also use the fudametal coutig piciple to detemie the umbe of sequeces. Sice the lettes caot be epeated, we have thee choices fo the fist lette, two choices fo the secod lette, ad oe choice fo the thid lette. Theefoe, the fudametal coutig piciple gives us = 6. We ca wite this equatio usig factoial otatio as! = 6. Factoial otatio is defied as! = ( ) ( ). Two impotat defiitios ae! = ad 0! =. agemets like these, whee ode is impotat ad o elemet is epeated, ae called pemutatios. pemutatio of a set of elemets is a odeed aagemet whee each elemet is used oce. Example Give five lettes {,,, D, E}, fid the umbe of fou-lette sequeces possible. Fom the fudametal coutig piciple, we have 5 =.

4 We ofte ecoute situatios like this oe, whee we have a set of objects ad we ae selectig objects to fom pemutatios. We efe to this as pemutatios of objects take at a time, ad we wite it as. Theefoe, example ca also be asweed as: The umbe of fou-lette sequeces is 5 =. Let s defie. The umbe of pemutatios of objects take at a time is: ) ) )... ) (which is the same as the fudametal coutig piciple), o!, whee ad ae atual umbes. )! We ca show that this fomula is the same as the fist oe:! )! ) )... ) ) )... ) ) ) )... ). You should udestad both fomulas ad feel comfotable applyig eithe oe. Example 5 ompute 6 usig both fomulas. Fist fomula: 6 5 =. 6! (6 5 ) Secod fomula: 6 5.! ( ) Example 6 You have math books ad 5 histoy books to put o a shelf that has 5 slots. I how may ways ca the books be shelved if the fist thee slots ae filled with math books ad the ext two slots ae filled with histoy books? Fist we detemie the umbe of ways the math books ca be aaged. This is a pemutatio of objects take at a time, o : = =. Next we detemie the umbe of ways the histoy books ca be aaged. This is a pemutatio of 5 objects take at a time, o 5 : 5 = 5 =.

5 Now we use the fudametal coutig piciple. Sice thee ae ways to aage the math books ad ways to aage the histoy books, the total umbe of ways to aage the math ad histoy books is, o 80. ombiatios Suppose that we have a set of thee lettes {,, }, ad we ae asked to make twolette sequeces. We have six pemutatios: Now suppose we have a goup of thee people {,, }, l, ob, ad his, espectively, ad we ae asked to fom committees of two people each. This time we have oly thee committees: Whe fomig committees, the ode is ot impotat because the committee that has l ad ob is o diffeet fom the committee that has ob ad l. s a esult, we have oly thee committees, ot six. Fomig sequeces is a example of pemutatios, while fomig committees is a example of combiatios. emutatios ae those aagemets whee ode is impotat, while combiatios ae those aagemets whee ode is ot sigificat. Recall that epesets the umbe of combiatios of objects take at a time. Now let s look at a situatio i which we eed to detemie the elatioship betwee the umbe of combiatios ad the umbe of pemutatios. Suppose we wat to detemie the umbe of pemutatios of lettes {,,, D} take at a time ( ). We kow that =, ad list all pemutatios: D D D D D D D D D D D D D D D D D D 5

6 If we wat to detemie the umbe of combiatios of lettes {,,, D} take at a time, we see that thee ae oly fou sice ode does ot matte. To detemie the umbe of combiatio of objects take at a time, we ca fist detemie the umbe of pemutatios of objects take at a time ad the divide by the umbe of pemutatios fo ay objects take at a time. So i this case, 6. We divide by 6 ( ) because oce we have the thee specific lettes, we ae ot coceed with the ode; so, we divide out the 6 diffeet odes of lettes take at a time. The fomal defiitio of a combiatio is a set of elemets i a aagemet whee each elemet is used oce ad ode is ot impotat. The umbe of combiatios of objects take at a time is witte..!, whee ad ae atual umbes. )!.! Notice that Example 7 ompute 5.! gives )! ad! gives. 5 (5 5! )! 5!!! 5 ( )( ) 0. ombiatios Ivolvig Seveal Sets So fa we have solved the basic combiatio poblem of objects chose fom diffeet objects. Now we will coside moe-complex poblems. Example 8 How may five-peso committees cosistig of me ad wome ca be chose fom a goup of me ad wome? Fist we coside the umbe of combiatios of me chose at a time ( ): = 6. Next we coside the umbe of combiatios of wome chose at a time ( ): =. 6

7 Sice thee ae 6 ways of choosig me ad ways of choosig wome, the fudametal coutig piciple gives us the umbe of five-peso committees: 6 =. obabilities Ivolvig ombiatios Example 9 high school club cosists of feshme, 5 sophomoes, 5 juios, ad 6 seios. What is the pobability that a committee of people chose at adom icludes oe studet fom each class? The total umbe of committees possible is sice thee ae studets i all ad we wat to select : =,85. The umbe of combiatios of feshma take at a time is =. The umbe of combiatios of 5 sophomoes take at a time is 5 = 5. The umbe of combiatios of 5 juios take at a time is 5 = 5. The umbe of combiatios of 6 juios take at a time is 6 = 6. Usig the fudametal coutig piciple, the umbe of committees is = 600. Example 0 high school club cosists of feshme, 5 sophomoes, 5 juios, ad 6 seios. What is the pobability that a committee of people chose at adom icludes at least oe seio? The total umbe of committees possible is sice thee ae studets i all ad we wat to select : =,85. We wat the committee to cotai at least oe seio, so it could cotai exactly oe seio, exactly two seios, exactly thee seios, o exactly fou seios. Fidig the pobability that the committee cotais at least oe seio equies us to fid the pobability fo each of the fou cases ad the use the additio piciple sice these fou possibilities ae disjoit evets. 6 6,85 8,85 (exactly oe seio) = (exactly two seios) = ,85 65,85 7

8 ,85 80,85 (exactly thee seios) = (exactly fou seios) = ,85 5,85 We kow that (at least oe seio) = (exactly oe seio) + (exactly two seios) + (exactly thee seios) + (exactly fou seios), so: (at least oe seio) = = We ca compute this pobability i a much moe efficiet mae, howeve, by usig the complemet of the evet at least oe seio. The complemet is that the committee cotais o seios (the oly othe possible outcome): (at least oe seio) = (o seios) (at least oe seio) 6 0,00, Whe dealig with pobability situatios ivolvig at least oe, the most efficiet way to detemie the pobability is to use the complemetay evet oe. This kowledge aticle is adapted fom the followig souce: Sekho, Rupide. "Sets ad outig." oexios. July,. 8

= 5! 3! 2! = 5! 3! (5 3)!. In general, the number of different groups of r items out of n items (when the order is ignored) is given by n!

= 5! 3! 2! = 5! 3! (5 3)!. In general, the number of different groups of r items out of n items (when the order is ignored) is given by n! 0 Combiatoial Aalysis Copyight by Deiz Kalı 4 Combiatios Questio 4 What is the diffeece betwee the followig questio i How may 3-lette wods ca you wite usig the lettes A, B, C, D, E ii How may 3-elemet

More information

Consider unordered sample of size r. This sample can be used to make r! Ordered samples (r! permutations). unordered sample

Consider unordered sample of size r. This sample can be used to make r! Ordered samples (r! permutations). unordered sample Uodeed Samples without Replacemet oside populatio of elemets a a... a. y uodeed aagemet of elemets is called a uodeed sample of size. Two uodeed samples ae diffeet oly if oe cotais a elemet ot cotaied

More information

MATH Midterm Solutions

MATH Midterm Solutions MATH 2113 - Midtem Solutios Febuay 18 1. A bag of mables cotais 4 which ae ed, 4 which ae blue ad 4 which ae gee. a How may mables must be chose fom the bag to guaatee that thee ae the same colou? We ca

More information

4. PERMUTATIONS AND COMBINATIONS

4. PERMUTATIONS AND COMBINATIONS 4. PERMUTATIONS AND COMBINATIONS PREVIOUS EAMCET BITS 1. The umbe of ways i which 13 gold cois ca be distibuted amog thee pesos such that each oe gets at least two gold cois is [EAMCET-000] 1) 3 ) 4 3)

More information

The number of r element subsets of a set with n r elements

The number of r element subsets of a set with n r elements Popositio: is The umbe of elemet subsets of a set with elemets Poof: Each such subset aises whe we pick a fist elemet followed by a secod elemet up to a th elemet The umbe of such choices is P But this

More information

CHAPTER 5 : SERIES. 5.2 The Sum of a Series Sum of Power of n Positive Integers Sum of Series of Partial Fraction Difference Method

CHAPTER 5 : SERIES. 5.2 The Sum of a Series Sum of Power of n Positive Integers Sum of Series of Partial Fraction Difference Method CHAPTER 5 : SERIES 5.1 Seies 5. The Sum of a Seies 5..1 Sum of Powe of Positive Iteges 5.. Sum of Seies of Patial Factio 5..3 Diffeece Method 5.3 Test of covegece 5.3.1 Divegece Test 5.3. Itegal Test 5.3.3

More information

ICS141: Discrete Mathematics for Computer Science I

ICS141: Discrete Mathematics for Computer Science I Uivesity of Hawaii ICS141: Discete Mathematics fo Compute Sciece I Dept. Ifomatio & Compute Sci., Uivesity of Hawaii Ja Stelovsy based o slides by D. Bae ad D. Still Oigials by D. M. P. Fa ad D. J.L. Goss

More information

Counting Functions and Subsets

Counting Functions and Subsets CHAPTER 1 Coutig Fuctios ad Subsets This chapte of the otes is based o Chapte 12 of PJE See PJE p144 Hee ad below, the efeeces to the PJEccles book ae give as PJE The goal of this shot chapte is to itoduce

More information

MATH /19: problems for supervision in week 08 SOLUTIONS

MATH /19: problems for supervision in week 08 SOLUTIONS MATH10101 2018/19: poblems fo supevisio i week 08 Q1. Let A be a set. SOLUTIONS (i Pove that the fuctio c: P(A P(A, defied by c(x A \ X, is bijective. (ii Let ow A be fiite, A. Use (i to show that fo each

More information

The Pigeonhole Principle 3.4 Binomial Coefficients

The Pigeonhole Principle 3.4 Binomial Coefficients Discete M athematic Chapte 3: Coutig 3. The Pigeohole Piciple 3.4 Biomial Coefficiets D Patic Cha School of Compute Sciece ad Egieeig South Chia Uivesity of Techology Ageda Ch 3. The Pigeohole Piciple

More information

PERMUTATIONS AND COMBINATIONS

PERMUTATIONS AND COMBINATIONS Pemutatios Ad ombiatios MODULE - I 7 PERMUTATIONS AND OMBINATIONS The othe day, I wated to tavel fom Bagaloe to Allahabad by tai. Thee is o diect tai fom Bagaloe to Allahabad, but thee ae tais fom Bagaloe

More information

Permutations and Combinations

Permutations and Combinations Pemutatios ad ombiatios Fudametal piciple of coutig Pemutatio Factoial otatio P!! ombiatio This uit facilitates you i, statig the fudametal piciple of coutig. defiig pemutatio ad combiatio. usig factoial

More information

Ch 3.4 Binomial Coefficients. Pascal's Identit y and Triangle. Chapter 3.2 & 3.4. South China University of Technology

Ch 3.4 Binomial Coefficients. Pascal's Identit y and Triangle. Chapter 3.2 & 3.4. South China University of Technology Disc ete Mathem atic Chapte 3: Coutig 3. The Pigeohole Piciple 3.4 Biomial Coefficiets D Patic Cha School of Compute Sciece ad Egieeig South Chia Uivesity of Techology Pigeohole Piciple Suppose that a

More information

a) The average (mean) of the two fractions is halfway between them: b) The answer is yes. Assume without loss of generality that p < r.

a) The average (mean) of the two fractions is halfway between them: b) The answer is yes. Assume without loss of generality that p < r. Solutios to MAML Olympiad Level 00. Factioated a) The aveage (mea) of the two factios is halfway betwee them: p ps+ q ps+ q + q s qs qs b) The aswe is yes. Assume without loss of geeality that p

More information

THE ANALYTIC LARGE SIEVE

THE ANALYTIC LARGE SIEVE THE ANALYTIC LAGE SIEVE 1. The aalytic lage sieve I the last lectue we saw how to apply the aalytic lage sieve to deive a aithmetic fomulatio of the lage sieve, which we applied to the poblem of boudig

More information

Permutations, Combinations, and the Binomial Theorem

Permutations, Combinations, and the Binomial Theorem Permutatios, ombiatios, ad the Biomial Theorem Sectio Permutatios outig methods are used to determie the umber of members of a specific set as well as outcomes of a evet. There are may differet ways to

More information

ELEMENTARY AND COMPOUND EVENTS PROBABILITY

ELEMENTARY AND COMPOUND EVENTS PROBABILITY Euopea Joual of Basic ad Applied Scieces Vol. 5 No., 08 ELEMENTARY AND COMPOUND EVENTS PROBABILITY William W.S. Che Depatmet of Statistics The Geoge Washigto Uivesity Washigto D.C. 003 E-mail: williamwsche@gmail.com

More information

4. PERMUTATIONS AND COMBINATIONS Quick Review

4. PERMUTATIONS AND COMBINATIONS Quick Review 4 ERMUTATIONS AND COMBINATIONS Quick Review A aagemet that ca be fomed by takig some o all of a fiite set of thigs (o objects) is called a emutatio A emutatio is said to be a liea emutatio if the objects

More information

2012 GCE A Level H2 Maths Solution Paper Let x,

2012 GCE A Level H2 Maths Solution Paper Let x, GCE A Level H Maths Solutio Pape. Let, y ad z be the cost of a ticet fo ude yeas, betwee ad 5 yeas, ad ove 5 yeas categoies espectively. 9 + y + 4z =. 7 + 5y + z = 8. + 4y + 5z = 58.5 Fo ude, ticet costs

More information

Chapter 2 Sampling distribution

Chapter 2 Sampling distribution [ 05 STAT] Chapte Samplig distibutio. The Paamete ad the Statistic Whe we have collected the data, we have a whole set of umbes o desciptios witte dow o a pape o stoed o a compute file. We ty to summaize

More information

Disjoint Sets { 9} { 1} { 11} Disjoint Sets (cont) Operations. Disjoint Sets (cont) Disjoint Sets (cont) n elements

Disjoint Sets { 9} { 1} { 11} Disjoint Sets (cont) Operations. Disjoint Sets (cont) Disjoint Sets (cont) n elements Disjoit Sets elemets { x, x, } X =, K Opeatios x Patitioed ito k sets (disjoit sets S, S,, K Fid-Set(x - etu set cotaiig x Uio(x,y - make a ew set by combiig the sets cotaiig x ad y (destoyig them S k

More information

BINOMIAL THEOREM An expression consisting of two terms, connected by + or sign is called a

BINOMIAL THEOREM An expression consisting of two terms, connected by + or sign is called a BINOMIAL THEOREM hapte 8 8. Oveview: 8.. A epessio cosistig of two tems, coected by + o sig is called a biomial epessio. Fo eample, + a, y,,7 4 5y, etc., ae all biomial epessios. 8.. Biomial theoem If

More information

Auchmuty High School Mathematics Department Sequences & Series Notes Teacher Version

Auchmuty High School Mathematics Department Sequences & Series Notes Teacher Version equeces ad eies Auchmuty High chool Mathematics Depatmet equeces & eies Notes Teache Vesio A sequece takes the fom,,7,0,, while 7 0 is a seies. Thee ae two types of sequece/seies aithmetic ad geometic.

More information

Advanced Physical Geodesy

Advanced Physical Geodesy Supplemetal Notes Review of g Tems i Moitz s Aalytic Cotiuatio Method. Advaced hysical Geodesy GS887 Chistophe Jekeli Geodetic Sciece The Ohio State Uivesity 5 South Oval Mall Columbus, OH 4 7 The followig

More information

BINOMIAL THEOREM NCERT An expression consisting of two terms, connected by + or sign is called a

BINOMIAL THEOREM NCERT An expression consisting of two terms, connected by + or sign is called a 8. Oveview: 8.. A epessio cosistig of two tems, coected by + o sig is called a biomial epessio. Fo eample, + a, y,,7 4, etc., ae all biomial 5y epessios. 8.. Biomial theoem BINOMIAL THEOREM If a ad b ae

More information

By the end of this section you will be able to prove the Chinese Remainder Theorem apply this theorem to solve simultaneous linear congruences

By the end of this section you will be able to prove the Chinese Remainder Theorem apply this theorem to solve simultaneous linear congruences Chapte : Theoy of Modula Aithmetic 8 Sectio D Chiese Remaide Theoem By the ed of this sectio you will be able to pove the Chiese Remaide Theoem apply this theoem to solve simultaeous liea cogueces The

More information

DANIEL YAQUBI, MADJID MIRZAVAZIRI AND YASIN SAEEDNEZHAD

DANIEL YAQUBI, MADJID MIRZAVAZIRI AND YASIN SAEEDNEZHAD MIXED -STIRLING NUMERS OF THE SEOND KIND DANIEL YAQUI, MADJID MIRZAVAZIRI AND YASIN SAEEDNEZHAD Abstact The Stilig umbe of the secod id { } couts the umbe of ways to patitio a set of labeled balls ito

More information

Lecture 6: October 16, 2017

Lecture 6: October 16, 2017 Ifomatio ad Codig Theoy Autum 207 Lectue: Madhu Tulsiai Lectue 6: Octobe 6, 207 The Method of Types Fo this lectue, we will take U to be a fiite uivese U, ad use x (x, x 2,..., x to deote a sequece of

More information

3.1 Counting Principles

3.1 Counting Principles 3.1 Coutig Priciples Goal: Cout the umber of objects i a set. Notatio: Whe S is a set, S deotes the umber of objects i the set. This is also called S s cardiality. Additio Priciple: Whe you wat to cout

More information

Permutations and Combinations

Permutations and Combinations Massachusetts Istitute of Techology 6.042J/18.062J, Fall 02: Mathematics fo Compute Sciece Pof. Albet Meye ad D. Radhika Nagpal Couse Notes 9 Pemutatios ad Combiatios I Notes 8, we saw a vaiety of techiques

More information

Lecture 24: Observability and Constructibility

Lecture 24: Observability and Constructibility ectue 24: Obsevability ad Costuctibility 7 Obsevability ad Costuctibility Motivatio: State feedback laws deped o a kowledge of the cuet state. I some systems, xt () ca be measued diectly, e.g., positio

More information

KEY. Math 334 Midterm II Fall 2007 section 004 Instructor: Scott Glasgow

KEY. Math 334 Midterm II Fall 2007 section 004 Instructor: Scott Glasgow KEY Math 334 Midtem II Fall 7 sectio 4 Istucto: Scott Glasgow Please do NOT wite o this exam. No cedit will be give fo such wok. Rathe wite i a blue book, o o you ow pape, pefeably egieeig pape. Wite you

More information

( ) ( ) ( ) ( ) Solved Examples. JEE Main/Boards = The total number of terms in the expansion are 8.

( ) ( ) ( ) ( ) Solved Examples. JEE Main/Boards = The total number of terms in the expansion are 8. Mathematics. Solved Eamples JEE Mai/Boads Eample : Fid the coefficiet of y i c y y Sol: By usig fomula of fidig geeal tem we ca easily get coefficiet of y. I the biomial epasio, ( ) th tem is c T ( y )

More information

EDEXCEL NATIONAL CERTIFICATE UNIT 28 FURTHER MATHEMATICS FOR TECHNICIANS OUTCOME 2- ALGEBRAIC TECHNIQUES TUTORIAL 1 - PROGRESSIONS

EDEXCEL NATIONAL CERTIFICATE UNIT 28 FURTHER MATHEMATICS FOR TECHNICIANS OUTCOME 2- ALGEBRAIC TECHNIQUES TUTORIAL 1 - PROGRESSIONS EDEXCEL NATIONAL CERTIFICATE UNIT 8 FURTHER MATHEMATICS FOR TECHNICIANS OUTCOME - ALGEBRAIC TECHNIQUES TUTORIAL - PROGRESSIONS CONTENTS Be able to apply algebaic techiques Aithmetic pogessio (AP): fist

More information

Discussion 02 Solutions

Discussion 02 Solutions STAT 400 Discussio 0 Solutios Spig 08. ~.5 ~.6 At the begiig of a cetai study of a goup of pesos, 5% wee classified as heavy smoes, 30% as light smoes, ad 55% as osmoes. I the fiveyea study, it was detemied

More information

Section 5.1 The Basics of Counting

Section 5.1 The Basics of Counting 1 Sectio 5.1 The Basics of Coutig Combiatorics, the study of arragemets of objects, is a importat part of discrete mathematics. I this chapter, we will lear basic techiques of coutig which has a lot of

More information

It is always the case that unions, intersections, complements, and set differences are preserved by the inverse image of a function.

It is always the case that unions, intersections, complements, and set differences are preserved by the inverse image of a function. MATH 532 Measurable Fuctios Dr. Neal, WKU Throughout, let ( X, F, µ) be a measure space ad let (!, F, P ) deote the special case of a probability space. We shall ow begi to study real-valued fuctios defied

More information

ON EUCLID S AND EULER S PROOF THAT THE NUMBER OF PRIMES IS INFINITE AND SOME APPLICATIONS

ON EUCLID S AND EULER S PROOF THAT THE NUMBER OF PRIMES IS INFINITE AND SOME APPLICATIONS Joual of Pue ad Alied Mathematics: Advaces ad Alicatios Volume 0 Numbe 03 Pages 5-58 ON EUCLID S AND EULER S PROOF THAT THE NUMBER OF PRIMES IS INFINITE AND SOME APPLICATIONS ALI H HAKAMI Deatmet of Mathematics

More information

PROGRESSION AND SERIES

PROGRESSION AND SERIES INTRODUCTION PROGRESSION AND SERIES A gemet of umbes {,,,,, } ccodig to some well defied ule o set of ules is clled sequece Moe pecisely, we my defie sequece s fuctio whose domi is some subset of set of

More information

Multivector Functions

Multivector Functions I: J. Math. Aal. ad Appl., ol. 24, No. 3, c Academic Pess (968) 467 473. Multivecto Fuctios David Hestees I a pevious pape [], the fudametals of diffeetial ad itegal calculus o Euclidea -space wee expessed

More information

Lecture 3 : Concentration and Correlation

Lecture 3 : Concentration and Correlation Lectue 3 : Cocetatio ad Coelatio 1. Talagad s iequality 2. Covegece i distibutio 3. Coelatio iequalities 1. Talagad s iequality Cetifiable fuctios Let g : R N be a fuctio. The a fuctio f : 1 2 Ω Ω L Ω

More information

Using Difference Equations to Generalize Results for Periodic Nested Radicals

Using Difference Equations to Generalize Results for Periodic Nested Radicals Usig Diffeece Equatios to Geealize Results fo Peiodic Nested Radicals Chis Lyd Uivesity of Rhode Islad, Depatmet of Mathematics South Kigsto, Rhode Islad 2 2 2 2 2 2 2 π = + + +... Vieta (593) 2 2 2 =

More information

A NOTE ON DOMINATION PARAMETERS IN RANDOM GRAPHS

A NOTE ON DOMINATION PARAMETERS IN RANDOM GRAPHS Discussioes Mathematicae Gaph Theoy 28 (2008 335 343 A NOTE ON DOMINATION PARAMETERS IN RANDOM GRAPHS Athoy Boato Depatmet of Mathematics Wilfid Lauie Uivesity Wateloo, ON, Caada, N2L 3C5 e-mail: aboato@oges.com

More information

On randomly generated non-trivially intersecting hypergraphs

On randomly generated non-trivially intersecting hypergraphs O adomly geeated o-tivially itesectig hypegaphs Balázs Patkós Submitted: May 5, 009; Accepted: Feb, 010; Published: Feb 8, 010 Mathematics Subject Classificatio: 05C65, 05D05, 05D40 Abstact We popose two

More information

Progression. CATsyllabus.com. CATsyllabus.com. Sequence & Series. Arithmetic Progression (A.P.) n th term of an A.P.

Progression. CATsyllabus.com. CATsyllabus.com. Sequence & Series. Arithmetic Progression (A.P.) n th term of an A.P. Pogessio Sequece & Seies A set of umbes whose domai is a eal umbe is called a SEQUENCE ad sum of the sequece is called a SERIES. If a, a, a, a 4,., a, is a sequece, the the expessio a + a + a + a 4 + a

More information

Math 7409 Homework 2 Fall from which we can calculate the cycle index of the action of S 5 on pairs of vertices as

Math 7409 Homework 2 Fall from which we can calculate the cycle index of the action of S 5 on pairs of vertices as Math 7409 Hoewok 2 Fall 2010 1. Eueate the equivalece classes of siple gaphs o 5 vetices by usig the patte ivetoy as a guide. The cycle idex of S 5 actig o 5 vetices is 1 x 5 120 1 10 x 3 1 x 2 15 x 1

More information

What is Probability?

What is Probability? Quatificatio of ucertaity. What is Probability? Mathematical model for thigs that occur radomly. Radom ot haphazard, do t kow what will happe o ay oe experimet, but has a log ru order. The cocept of probability

More information

Summary: Binomial Expansion...! r. where

Summary: Binomial Expansion...! r. where Summy: Biomil Epsio 009 M Teo www.techmejcmth-sg.wes.com ) Re-cp of Additiol Mthemtics Biomil Theoem... whee )!!(! () The fomul is ville i MF so studets do ot eed to memoise it. () The fomul pplies oly

More information

ARRANGEMENTS IN A CIRCLE

ARRANGEMENTS IN A CIRCLE ARRANGEMENTS IN A CIRCLE Whe objects are arraged i a circle, the total umber of arragemets is reduced. The arragemet of (say) four people i a lie is easy ad o problem (if they liste of course!!). With

More information

SOME ARITHMETIC PROPERTIES OF OVERPARTITION K -TUPLES

SOME ARITHMETIC PROPERTIES OF OVERPARTITION K -TUPLES #A17 INTEGERS 9 2009), 181-190 SOME ARITHMETIC PROPERTIES OF OVERPARTITION K -TUPLES Deick M. Keiste Depatmet of Mathematics, Pe State Uivesity, Uivesity Pak, PA 16802 dmk5075@psu.edu James A. Selles Depatmet

More information

6.3 Testing Series With Positive Terms

6.3 Testing Series With Positive Terms 6.3. TESTING SERIES WITH POSITIVE TERMS 307 6.3 Testig Series With Positive Terms 6.3. Review of what is kow up to ow I theory, testig a series a i for covergece amouts to fidig the i= sequece of partial

More information

EXAMPLES. Leader in CBSE Coaching. Solutions of BINOMIAL THEOREM A.V.T.E. by AVTE (avte.in) Class XI

EXAMPLES. Leader in CBSE Coaching. Solutions of BINOMIAL THEOREM A.V.T.E. by AVTE (avte.in) Class XI avtei EXAMPLES Solutios of AVTE by AVTE (avtei) lass XI Leade i BSE oachig 1 avtei SHORT ANSWER TYPE 1 Fid the th tem i the epasio of 1 We have T 1 1 1 1 1 1 1 1 1 1 Epad the followig (1 + ) 4 Put 1 y

More information

( ) 1 Comparison Functions. α is strictly increasing since ( r) ( r ) α = for any positive real number c. = 0. It is said to belong to

( ) 1 Comparison Functions. α is strictly increasing since ( r) ( r ) α = for any positive real number c. = 0. It is said to belong to Compaiso Fuctios I this lesso, we study stability popeties of the oautoomous system = f t, x The difficulty is that ay solutio of this system statig at x( t ) depeds o both t ad t = x Thee ae thee special

More information

Electron states in a periodic potential. Assume the electrons do not interact with each other. Solve the single electron Schrodinger equation: KJ =

Electron states in a periodic potential. Assume the electrons do not interact with each other. Solve the single electron Schrodinger equation: KJ = Electo states i a peiodic potetial Assume the electos do ot iteact with each othe Solve the sigle electo Schodige equatio: 2 F h 2 + I U ( ) Ψ( ) EΨ( ). 2m HG KJ = whee U(+R)=U(), R is ay Bavais lattice

More information

Week 03 Discussion. 30% are serious, and 50% are stable. Of the critical ones, 30% die; of the serious, 10% die; and of the stable, 2% die.

Week 03 Discussion. 30% are serious, and 50% are stable. Of the critical ones, 30% die; of the serious, 10% die; and of the stable, 2% die. STAT 400 Wee 03 Discussio Fall 07. ~.5- ~.6- At the begiig of a cetai study of a gou of esos, 5% wee classified as heavy smoes, 30% as light smoes, ad 55% as osmoes. I the five-yea study, it was detemied

More information

9.7 Pascal s Formula and the Binomial Theorem

9.7 Pascal s Formula and the Binomial Theorem 592 Chapte 9 Coutig ad Pobability Example 971 Values of 97 Pascal s Fomula ad the Biomial Theoem I m vey well acquaited, too, with mattes mathematical, I udestad equatios both the simple ad quadatical

More information

On a Problem of Littlewood

On a Problem of Littlewood Ž. JOURAL OF MATHEMATICAL AALYSIS AD APPLICATIOS 199, 403 408 1996 ARTICLE O. 0149 O a Poblem of Littlewood Host Alze Mosbache Stasse 10, 51545 Waldbol, Gemay Submitted by J. L. Bee Received May 19, 1995

More information

On ARMA(1,q) models with bounded and periodically correlated solutions

On ARMA(1,q) models with bounded and periodically correlated solutions Reseach Repot HSC/03/3 O ARMA(,q) models with bouded ad peiodically coelated solutios Aleksade Weo,2 ad Agieszka Wy oma ska,2 Hugo Steihaus Cete, Woc aw Uivesity of Techology 2 Istitute of Mathematics,

More information

LESSON 15: COMPOUND INTEREST

LESSON 15: COMPOUND INTEREST High School: Expoeial Fuctios LESSON 15: COMPOUND INTEREST 1. You have see this fomula fo compoud ieest. Paamete P is the picipal amou (the moey you stat with). Paamete is the ieest ate pe yea expessed

More information

As stated by Laplace, Probability is common sense reduced to calculation.

As stated by Laplace, Probability is common sense reduced to calculation. Note: Hadouts DO NOT replace the book. I most cases, they oly provide a guidelie o topics ad a ituitive feel. The math details will be covered i class, so it is importat to atted class ad also you MUST

More information

Lecture 2: Stress. 1. Forces Surface Forces and Body Forces

Lecture 2: Stress. 1. Forces Surface Forces and Body Forces Lectue : Stess Geophysicists study pheomea such as seismicity, plate tectoics, ad the slow flow of ocks ad mieals called ceep. Oe way they study these pheomea is by ivestigatig the defomatio ad flow of

More information

Lesson 10: Limits and Continuity

Lesson 10: Limits and Continuity www.scimsacademy.com Lesso 10: Limits ad Cotiuity SCIMS Academy 1 Limit of a fuctio The cocept of limit of a fuctio is cetral to all other cocepts i calculus (like cotiuity, derivative, defiite itegrals

More information

Topic 5: Basics of Probability

Topic 5: Basics of Probability Topic 5: Jue 1, 2011 1 Itroductio Mathematical structures lie Euclidea geometry or algebraic fields are defied by a set of axioms. Mathematical reality is the developed through the itroductio of cocepts

More information

At the end of this topic, students should be able to understand the meaning of finite and infinite sequences and series, and use the notation u

At the end of this topic, students should be able to understand the meaning of finite and infinite sequences and series, and use the notation u Natioal Jio College Mathematics Depatmet 00 Natioal Jio College 00 H Mathematics (Seio High ) Seqeces ad Seies (Lecte Notes) Topic : Seqeces ad Seies Objectives: At the ed of this topic, stdets shold be

More information

Infinite Sequences and Series

Infinite Sequences and Series Chapter 6 Ifiite Sequeces ad Series 6.1 Ifiite Sequeces 6.1.1 Elemetary Cocepts Simply speakig, a sequece is a ordered list of umbers writte: {a 1, a 2, a 3,...a, a +1,...} where the elemets a i represet

More information

Chapter Vectors

Chapter Vectors Chapter 4. Vectors fter readig this chapter you should be able to:. defie a vector. add ad subtract vectors. fid liear combiatios of vectors ad their relatioship to a set of equatios 4. explai what it

More information

Strong Result for Level Crossings of Random Polynomials

Strong Result for Level Crossings of Random Polynomials IOSR Joual of haacy ad Biological Scieces (IOSR-JBS) e-issn:78-8, p-issn:19-7676 Volue 11, Issue Ve III (ay - Ju16), 1-18 wwwiosjoualsog Stog Result fo Level Cossigs of Rado olyoials 1 DKisha, AK asigh

More information

Chapter 1 : Combinatorial Analysis

Chapter 1 : Combinatorial Analysis STAT/MATH 394 A - PROBABILITY I UW Autum Quarter 205 Néhémy Lim Chapter : Combiatorial Aalysis A major brach of combiatorial aalysis called eumerative combiatorics cosists of studyig methods for coutig

More information

Chapter 0. Review of set theory. 0.1 Sets

Chapter 0. Review of set theory. 0.1 Sets Chapter 0 Review of set theory Set theory plays a cetral role i the theory of probability. Thus, we will ope this course with a quick review of those otios of set theory which will be used repeatedly.

More information

CHAPTER 5. Theory and Solution Using Matrix Techniques

CHAPTER 5. Theory and Solution Using Matrix Techniques A SERIES OF CLASS NOTES FOR 2005-2006 TO INTRODUCE LINEAR AND NONLINEAR PROBLEMS TO ENGINEERS, SCIENTISTS, AND APPLIED MATHEMATICIANS DE CLASS NOTES 3 A COLLECTION OF HANDOUTS ON SYSTEMS OF ORDINARY DIFFERENTIAL

More information

(ii) Two-permutations of {a, b, c}. Answer. (B) P (3, 3) = 3! (C) 3! = 6, and there are 6 items in (A). ... Answer.

(ii) Two-permutations of {a, b, c}. Answer. (B) P (3, 3) = 3! (C) 3! = 6, and there are 6 items in (A). ... Answer. SOLUTIONS Homewor 5 Due /6/19 Exercise. (a Cosider the set {a, b, c}. For each of the followig, (A list the objects described, (B give a formula that tells you how may you should have listed, ad (C verify

More information

Intermediate Math Circles November 4, 2009 Counting II

Intermediate Math Circles November 4, 2009 Counting II Uiversity of Waterloo Faculty of Mathematics Cetre for Educatio i Mathematics ad Computig Itermediate Math Circles November 4, 009 Coutig II Last time, after lookig at the product rule ad sum rule, we

More information

Randomized Algorithms I, Spring 2018, Department of Computer Science, University of Helsinki Homework 1: Solutions (Discussed January 25, 2018)

Randomized Algorithms I, Spring 2018, Department of Computer Science, University of Helsinki Homework 1: Solutions (Discussed January 25, 2018) Radomized Algorithms I, Sprig 08, Departmet of Computer Sciece, Uiversity of Helsiki Homework : Solutios Discussed Jauary 5, 08). Exercise.: Cosider the followig balls-ad-bi game. We start with oe black

More information

Math 155 (Lecture 3)

Math 155 (Lecture 3) Math 55 (Lecture 3) September 8, I this lecture, we ll cosider the aswer to oe of the most basic coutig problems i combiatorics Questio How may ways are there to choose a -elemet subset of the set {,,,

More information

Lecture Overview. 2 Permutations and Combinations. n(n 1) (n (k 1)) = n(n 1) (n k + 1) =

Lecture Overview. 2 Permutations and Combinations. n(n 1) (n (k 1)) = n(n 1) (n k + 1) = COMPSCI 230: Discrete Mathematics for Computer Sciece April 8, 2019 Lecturer: Debmalya Paigrahi Lecture 22 Scribe: Kevi Su 1 Overview I this lecture, we begi studyig the fudametals of coutig discrete objects.

More information

Sets and Probabilistic Models

Sets and Probabilistic Models ets ad Probabilistic Models Berli Che Departmet of Computer ciece & Iformatio Egieerig Natioal Taiwa Normal iversity Referece: - D. P. Bertsekas, J. N. Tsitsiklis, Itroductio to Probability, ectios 1.1-1.2

More information

Lecture 4: Unique-SAT, Parity-SAT, and Approximate Counting

Lecture 4: Unique-SAT, Parity-SAT, and Approximate Counting Advaced Complexity Theory Sprig 206 Lecture 4: Uique-SAT, Parity-SAT, ad Approximate Coutig Prof. Daa Moshkovitz Scribe: Aoymous Studet Scribe Date: Fall 202 Overview I this lecture we begi talkig about

More information

Strong Result for Level Crossings of Random Polynomials. Dipty Rani Dhal, Dr. P. K. Mishra. Department of Mathematics, CET, BPUT, BBSR, ODISHA, INDIA

Strong Result for Level Crossings of Random Polynomials. Dipty Rani Dhal, Dr. P. K. Mishra. Department of Mathematics, CET, BPUT, BBSR, ODISHA, INDIA Iteatioal Joual of Reseach i Egieeig ad aageet Techology (IJRET) olue Issue July 5 Available at http://wwwijetco/ Stog Result fo Level Cossigs of Rado olyoials Dipty Rai Dhal D K isha Depatet of atheatics

More information

It is often useful to approximate complicated functions using simpler ones. We consider the task of approximating a function by a polynomial.

It is often useful to approximate complicated functions using simpler ones. We consider the task of approximating a function by a polynomial. Taylor Polyomials ad Taylor Series It is ofte useful to approximate complicated fuctios usig simpler oes We cosider the task of approximatig a fuctio by a polyomial If f is at least -times differetiable

More information

Einstein Classes, Unit No. 102, 103, Vardhman Ring Road Plaza, Vikas Puri Extn., Outer Ring Road New Delhi , Ph. : ,

Einstein Classes, Unit No. 102, 103, Vardhman Ring Road Plaza, Vikas Puri Extn., Outer Ring Road New Delhi , Ph. : , MB BINOMIAL THEOREM Biomial Epessio : A algebaic epessio which cotais two dissimila tems is called biomial epessio Fo eample :,,, etc / ( ) Statemet of Biomial theoem : If, R ad N, the : ( + ) = a b +

More information

CHAPTER I: Vector Spaces

CHAPTER I: Vector Spaces CHAPTER I: Vector Spaces Sectio 1: Itroductio ad Examples This first chapter is largely a review of topics you probably saw i your liear algebra course. So why cover it? (1) Not everyoe remembers everythig

More information

Conditional Convergence of Infinite Products

Conditional Convergence of Infinite Products Coditioal Covegece of Ifiite Poducts William F. Tech Ameica Mathematical Mothly 106 1999), 646-651 I this aticle we evisit the classical subject of ifiite poducts. Fo stadad defiitios ad theoems o this

More information

Other quantum algorithms

Other quantum algorithms Chapte 3 Othe uatum agoithms 3. Quick emide of Gove s agoithm We peset hee a uick emide of Gove s agoithm. Iput: a fuctio f : {0,}! {0,}. Goa: fid x such that f (x) =. Seach pobem We have a uatum access

More information

Putnam Training Exercise Counting, Probability, Pigeonhole Principle (Answers)

Putnam Training Exercise Counting, Probability, Pigeonhole Principle (Answers) Putam Traiig Exercise Coutig, Probability, Pigeohole Pricile (Aswers) November 24th, 2015 1. Fid the umber of iteger o-egative solutios to the followig Diohatie equatio: x 1 + x 2 + x 3 + x 4 + x 5 = 17.

More information

Summary: Congruences. j=1. 1 Here we use the Mathematica syntax for the function. In Maple worksheets, the function

Summary: Congruences. j=1. 1 Here we use the Mathematica syntax for the function. In Maple worksheets, the function Summary: Cogrueces j whe divided by, ad determiig the additive order of a iteger mod. As described i the Prelab sectio, cogrueces ca be thought of i terms of coutig with rows, ad for some questios this

More information

Sets and Probabilistic Models

Sets and Probabilistic Models ets ad Probabilistic Models Berli Che Departmet of Computer ciece & Iformatio Egieerig Natioal Taiwa Normal Uiversity Referece: - D. P. Bertsekas, J. N. Tsitsiklis, Itroductio to Probability, ectios 1.1-1.2

More information

MATHS FOR ENGINEERS ALGEBRA TUTORIAL 8 MATHEMATICAL PROGRESSIONS AND SERIES

MATHS FOR ENGINEERS ALGEBRA TUTORIAL 8 MATHEMATICAL PROGRESSIONS AND SERIES MATHS FOR ENGINEERS ALGEBRA TUTORIAL 8 MATHEMATICAL PROGRESSIONS AND SERIES O completio of this ttoial yo shold be able to do the followig. Eplai aithmetical ad geometic pogessios. Eplai factoial otatio

More information

Math 166 Week-in-Review - S. Nite 11/10/2012 Page 1 of 5 WIR #9 = 1+ r eff. , where r. is the effective interest rate, r is the annual

Math 166 Week-in-Review - S. Nite 11/10/2012 Page 1 of 5 WIR #9 = 1+ r eff. , where r. is the effective interest rate, r is the annual Math 66 Week-i-Review - S. Nite // Page of Week i Review #9 (F-F.4, 4.-4.4,.-.) Simple Iteest I = Pt, whee I is the iteest, P is the picipal, is the iteest ate, ad t is the time i yeas. P( + t), whee A

More information

UNIT 2 DIFFERENT APPROACHES TO PROBABILITY THEORY

UNIT 2 DIFFERENT APPROACHES TO PROBABILITY THEORY UNIT 2 DIFFERENT APPROACHES TO PROBABILITY THEORY Structure 2.1 Itroductio Objectives 2.2 Relative Frequecy Approach ad Statistical Probability 2. Problems Based o Relative Frequecy 2.4 Subjective Approach

More information

Math 113 Exam 3 Practice

Math 113 Exam 3 Practice Math Exam Practice Exam will cover.-.9. This sheet has three sectios. The first sectio will remid you about techiques ad formulas that you should kow. The secod gives a umber of practice questios for you

More information

COMP 2804 Solutions Assignment 1

COMP 2804 Solutions Assignment 1 COMP 2804 Solutios Assiget 1 Questio 1: O the first page of your assiget, write your ae ad studet uber Solutio: Nae: Jaes Bod Studet uber: 007 Questio 2: I Tic-Tac-Toe, we are give a 3 3 grid, cosistig

More information

Chapter 8 Complex Numbers

Chapter 8 Complex Numbers Chapte 8 Complex Numbes Motivatio: The ae used i a umbe of diffeet scietific aeas icludig: sigal aalsis, quatum mechaics, elativit, fluid damics, civil egieeig, ad chaos theo (factals. 8.1 Cocepts - Defiitio

More information

SOLUTIONS ( ) ( )! ( ) ( ) ( ) ( )! ( ) ( ) ( ) ( ) n r. r ( Pascal s equation ). n 1. Stepanov Dalpiaz

SOLUTIONS ( ) ( )! ( ) ( ) ( ) ( )! ( ) ( ) ( ) ( ) n r. r ( Pascal s equation ). n 1. Stepanov Dalpiaz STAT UIU Pctice Poblems # SOLUTIONS Stepov Dlpiz The followig e umbe of pctice poblems tht my be helpful fo completig the homewo, d will liely be vey useful fo studyig fo ems...-.-.- Pove (show) tht. (

More information

Injections, Surjections, and the Pigeonhole Principle

Injections, Surjections, and the Pigeonhole Principle Ijectios, Surjectios, ad the Pigeohole Priciple 1 (10 poits Here we will come up with a sloppy boud o the umber of parethesisestigs (a (5 poits Describe a ijectio from the set of possible ways to est pairs

More information

Math 113 Exam 4 Practice

Math 113 Exam 4 Practice Math Exam 4 Practice Exam 4 will cover.-.. This sheet has three sectios. The first sectio will remid you about techiques ad formulas that you should kow. The secod gives a umber of practice questios for

More information

Axioms of Measure Theory

Axioms of Measure Theory MATH 532 Axioms of Measure Theory Dr. Neal, WKU I. The Space Throughout the course, we shall let X deote a geeric o-empty set. I geeral, we shall ot assume that ay algebraic structure exists o X so that

More information

Auchmuty High School Mathematics Department Advanced Higher Notes Teacher Version

Auchmuty High School Mathematics Department Advanced Higher Notes Teacher Version The Binomial Theoem Factoials Auchmuty High School Mathematics Depatment The calculations,, 6 etc. often appea in mathematics. They ae called factoials and have been given the notation n!. e.g. 6! 6!!!!!

More information

62. Power series Definition 16. (Power series) Given a sequence {c n }, the series. c n x n = c 0 + c 1 x + c 2 x 2 + c 3 x 3 +

62. Power series Definition 16. (Power series) Given a sequence {c n }, the series. c n x n = c 0 + c 1 x + c 2 x 2 + c 3 x 3 + 62. Power series Defiitio 16. (Power series) Give a sequece {c }, the series c x = c 0 + c 1 x + c 2 x 2 + c 3 x 3 + is called a power series i the variable x. The umbers c are called the coefficiets of

More information

Sequences. Notation. Convergence of a Sequence

Sequences. Notation. Convergence of a Sequence Sequeces A sequece is essetially just a list. Defiitio (Sequece of Real Numbers). A sequece of real umbers is a fuctio Z (, ) R for some real umber. Do t let the descriptio of the domai cofuse you; it

More information

Trial division, Pollard s p 1, Pollard s ρ, and Fermat s method. Christopher Koch 1. April 8, 2014

Trial division, Pollard s p 1, Pollard s ρ, and Fermat s method. Christopher Koch 1. April 8, 2014 Iteger Divisio Algorithm ad Cogruece Iteger Trial divisio,,, ad with itegers mod Iverses mod Multiplicatio ad GCD Iteger Christopher Koch 1 1 Departmet of Computer Sciece ad Egieerig CSE489/589 Algorithms

More information