SlideShare une entreprise Scribd logo
1  sur  40
THE BALLOT PROBLEM OF  MANY CANDIDATES
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
What is the Ballot problem? ,[object Object],The formula comes up to be . a voters for A b voters for B
Why is it interesting? ,[object Object],[object Object]
Objective To find the formula and proof of Ballot problem for many candidates.
In the case of two candidates (The Original Ballot problem)
Suppose   is the ballots of the  1 st   candidate.   is the ballots of the 2 nd   candidate, when   . Define   “1” as the ballot given to 1 st   candidate.   “ -1” as the ballot given to 2 nd   candidate. In the case of two Candidates
The number of ways to count the ballots for  required condition. The number of permutation of the sequence: such that the partial sum is always positive. The number of ways to walk on the lattice plane starting at (0,0) and finish at (a,b), and not allow pass through the line y=x except (0,0) = =
In the case of two Candidates
Reflection Principle “ Reflection principle” is use to count the number of path, one can show that the number of illegal ways which begin at (1,0) is equal to the number of ways begin at (0,1). It implies that, if we denote    as the number of ways as required:
Reflection Principle Figure 1 Figure 2
In the case of three Candidates
In the case of three Candidates
In the case of three Candidates Figure 3 Figure 4
How to count ?
How to count ?
[object Object],[object Object],[object Object],How to count ?
Example Counting Front View F(1) F(2) F(3) F(4) F(5)
Example Counting Side View S(1) S(2)
Example Counting Matching 2 2 1 1 1 S(2) 1 1 1 1 1 S(1) F(5) F(4) F(3) F(2) F(1) F(i) * S(j) F(1) F(2) F(3) F(4) F(5) S(1) S(2) 5 7 12 Total
Dynamic Programming
Counting (5,4) with D.P. y x x+y 1 1 1 1 1 1 1 4 3 2 1 0 0 9 5 2 0 0 0 14 5 0 0 0 0 14 0 0 0 0 0
Formula for three candidates
Definition   is the number of ways to count the ballot that correspond to the required condition  Lemma 1.1 Lemma 1.2 Formula for three candidates
Formula for three candidates Conjecture
Let Consider Use strong induction; given   is the “base” therefore Proof Hence, the base case is true.  Formula for three candidates
[object Object],[object Object],We will use this assumption to prove that  is true Formula for three candidates
Formula for three candidates
By strong induction, we get that, Formula for three candidates
Formula for n candidates
  is the number of ways to count the ballots of the n candidates such that, while the ballots are being counted, the winner will always get more ballots than the loser.  Definition   Lemma 3 Formula for n candidates
(base) n=2 n=k Mathematical Induction Sub - Strong Mathematical Induction (base) n=k-1 Proof
Formula for n candidates
Formula for n candidates
Formula for n candidates
By mathematical induction, Formula for n candidates
1. Think about the condition “never less than” instead of “always more than.” Development 2. What if we suppose that the ballots of the 3 rd  candidate don’t relate to anyone else?
Application In Biology ,[object Object],[object Object],[object Object],[object Object],[object Object]
Application In Cryptography Define the plaintext (code) used to send the data  Increases the security of the system.
Reference Chen Chuan-Chong and Koh Khee-Meng,  Principles and Techniques  in Combinatorics , World Scientific, 3rd ed., 1999.  Marc Renault,  Four Proofs of the Ballot Theorem,  U.S.A., 2007. Michael L. GARGANO, Lorraine L. LURIE Louis V. QUINTAS, and  Eric M. WAHL,  The Ballot Problem,  U.S.A.,2005. Miklos Bona, Unimodality,  Introduction to Enumerative Combinatorics,  McGrawHill, 2007. Sriram V. Pemmaraju, Steven S. Skienay,  A System for Exploring  Combinatorics and Graph Theory in Mathematica,  U.S.A., 2004.

Contenu connexe

Similaire à Math Project Presentation New

Ballot Problem for Many Candidates
Ballot Problem for Many CandidatesBallot Problem for Many Candidates
Ballot Problem for Many Candidatesguest838786
 
Lecture Notes MTH302 Before MTT Myers.docx
Lecture Notes MTH302 Before MTT Myers.docxLecture Notes MTH302 Before MTT Myers.docx
Lecture Notes MTH302 Before MTT Myers.docxRaghavaReddy449756
 
First session _Cracking the coding interview.pptx
First session _Cracking the coding interview.pptxFirst session _Cracking the coding interview.pptx
First session _Cracking the coding interview.pptxZilvinasAleksa
 
statiscs and probability math college to help student
statiscs and probability math college  to help studentstatiscs and probability math college  to help student
statiscs and probability math college to help studentcharlezeannprodonram
 
Discrete Math Lecture 01: Propositional Logic
Discrete Math Lecture 01: Propositional LogicDiscrete Math Lecture 01: Propositional Logic
Discrete Math Lecture 01: Propositional LogicIT Engineering Department
 
Analyzing experimental research data
Analyzing experimental research dataAnalyzing experimental research data
Analyzing experimental research dataAtula Ahuja
 
Bahan ajar materi peluang kelas viii
Bahan ajar materi peluang kelas viiiBahan ajar materi peluang kelas viii
Bahan ajar materi peluang kelas viiiMartiwiFarisa
 
Chapter 4 260110 044531
Chapter 4 260110 044531Chapter 4 260110 044531
Chapter 4 260110 044531guest25d353
 
ML.ppt
ML.pptML.ppt
ML.pptbutest
 
One.  Clark Heter is an industrial engineer at Lyons Products. He .docx
One.  Clark Heter is an industrial engineer at Lyons Products. He .docxOne.  Clark Heter is an industrial engineer at Lyons Products. He .docx
One.  Clark Heter is an industrial engineer at Lyons Products. He .docxhopeaustin33688
 
Probability distribution Function & Decision Trees in machine learning
Probability distribution Function  & Decision Trees in machine learningProbability distribution Function  & Decision Trees in machine learning
Probability distribution Function & Decision Trees in machine learningSadia Zafar
 

Similaire à Math Project Presentation New (20)

Ballot Problem for Many Candidates
Ballot Problem for Many CandidatesBallot Problem for Many Candidates
Ballot Problem for Many Candidates
 
Probability Assignment Help
Probability Assignment HelpProbability Assignment Help
Probability Assignment Help
 
Probability Assignment Help
Probability Assignment HelpProbability Assignment Help
Probability Assignment Help
 
Lecture Notes MTH302 Before MTT Myers.docx
Lecture Notes MTH302 Before MTT Myers.docxLecture Notes MTH302 Before MTT Myers.docx
Lecture Notes MTH302 Before MTT Myers.docx
 
Probability and Statistics - Week 1
Probability and Statistics - Week 1Probability and Statistics - Week 1
Probability and Statistics - Week 1
 
Basic concepts of probability
Basic concepts of probability Basic concepts of probability
Basic concepts of probability
 
First session _Cracking the coding interview.pptx
First session _Cracking the coding interview.pptxFirst session _Cracking the coding interview.pptx
First session _Cracking the coding interview.pptx
 
Counting
Counting  Counting
Counting
 
Mathematics Homework Help
Mathematics Homework HelpMathematics Homework Help
Mathematics Homework Help
 
statiscs and probability math college to help student
statiscs and probability math college  to help studentstatiscs and probability math college  to help student
statiscs and probability math college to help student
 
Discrete Math Lecture 01: Propositional Logic
Discrete Math Lecture 01: Propositional LogicDiscrete Math Lecture 01: Propositional Logic
Discrete Math Lecture 01: Propositional Logic
 
Analyzing experimental research data
Analyzing experimental research dataAnalyzing experimental research data
Analyzing experimental research data
 
ANOVA.ppt
ANOVA.pptANOVA.ppt
ANOVA.ppt
 
Bahan ajar materi peluang kelas viii
Bahan ajar materi peluang kelas viiiBahan ajar materi peluang kelas viii
Bahan ajar materi peluang kelas viii
 
Chapter 4 260110 044531
Chapter 4 260110 044531Chapter 4 260110 044531
Chapter 4 260110 044531
 
Probability Theory for Data Scientists
Probability Theory for Data ScientistsProbability Theory for Data Scientists
Probability Theory for Data Scientists
 
ML.ppt
ML.pptML.ppt
ML.ppt
 
One.  Clark Heter is an industrial engineer at Lyons Products. He .docx
One.  Clark Heter is an industrial engineer at Lyons Products. He .docxOne.  Clark Heter is an industrial engineer at Lyons Products. He .docx
One.  Clark Heter is an industrial engineer at Lyons Products. He .docx
 
Correcciòn ejerciciodocx
Correcciòn ejerciciodocxCorrecciòn ejerciciodocx
Correcciòn ejerciciodocx
 
Probability distribution Function & Decision Trees in machine learning
Probability distribution Function  & Decision Trees in machine learningProbability distribution Function  & Decision Trees in machine learning
Probability distribution Function & Decision Trees in machine learning
 

Dernier

Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024The Digital Insurer
 
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024The Digital Insurer
 
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEarley Information Science
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationSafe Software
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationRadu Cotescu
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsEnterprise Knowledge
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...Martijn de Jong
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking MenDelhi Call girls
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...Neo4j
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slidespraypatel2
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfEnterprise Knowledge
 
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsJoaquim Jorge
 
Advantages of Hiring UIUX Design Service Providers for Your Business
Advantages of Hiring UIUX Design Service Providers for Your BusinessAdvantages of Hiring UIUX Design Service Providers for Your Business
Advantages of Hiring UIUX Design Service Providers for Your BusinessPixlogix Infotech
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slidevu2urc
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)Gabriella Davis
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfsudhanshuwaghmare1
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreternaman860154
 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...apidays
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘RTylerCroy
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Miguel Araújo
 

Dernier (20)

Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
 
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024
 
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organization
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI Solutions
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slides
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
 
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and Myths
 
Advantages of Hiring UIUX Design Service Providers for Your Business
Advantages of Hiring UIUX Design Service Providers for Your BusinessAdvantages of Hiring UIUX Design Service Providers for Your Business
Advantages of Hiring UIUX Design Service Providers for Your Business
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slide
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
 

Math Project Presentation New

  • 1. THE BALLOT PROBLEM OF MANY CANDIDATES
  • 2.
  • 3.
  • 4.
  • 5. Objective To find the formula and proof of Ballot problem for many candidates.
  • 6. In the case of two candidates (The Original Ballot problem)
  • 7. Suppose is the ballots of the 1 st candidate. is the ballots of the 2 nd candidate, when . Define “1” as the ballot given to 1 st candidate. “ -1” as the ballot given to 2 nd candidate. In the case of two Candidates
  • 8. The number of ways to count the ballots for required condition. The number of permutation of the sequence: such that the partial sum is always positive. The number of ways to walk on the lattice plane starting at (0,0) and finish at (a,b), and not allow pass through the line y=x except (0,0) = =
  • 9. In the case of two Candidates
  • 10. Reflection Principle “ Reflection principle” is use to count the number of path, one can show that the number of illegal ways which begin at (1,0) is equal to the number of ways begin at (0,1). It implies that, if we denote as the number of ways as required:
  • 12. In the case of three Candidates
  • 13. In the case of three Candidates
  • 14. In the case of three Candidates Figure 3 Figure 4
  • 17.
  • 18. Example Counting Front View F(1) F(2) F(3) F(4) F(5)
  • 19. Example Counting Side View S(1) S(2)
  • 20. Example Counting Matching 2 2 1 1 1 S(2) 1 1 1 1 1 S(1) F(5) F(4) F(3) F(2) F(1) F(i) * S(j) F(1) F(2) F(3) F(4) F(5) S(1) S(2) 5 7 12 Total
  • 22. Counting (5,4) with D.P. y x x+y 1 1 1 1 1 1 1 4 3 2 1 0 0 9 5 2 0 0 0 14 5 0 0 0 0 14 0 0 0 0 0
  • 23. Formula for three candidates
  • 24. Definition is the number of ways to count the ballot that correspond to the required condition Lemma 1.1 Lemma 1.2 Formula for three candidates
  • 25. Formula for three candidates Conjecture
  • 26. Let Consider Use strong induction; given is the “base” therefore Proof Hence, the base case is true. Formula for three candidates
  • 27.
  • 28. Formula for three candidates
  • 29. By strong induction, we get that, Formula for three candidates
  • 30. Formula for n candidates
  • 31. is the number of ways to count the ballots of the n candidates such that, while the ballots are being counted, the winner will always get more ballots than the loser. Definition Lemma 3 Formula for n candidates
  • 32. (base) n=2 n=k Mathematical Induction Sub - Strong Mathematical Induction (base) n=k-1 Proof
  • 33. Formula for n candidates
  • 34. Formula for n candidates
  • 35. Formula for n candidates
  • 36. By mathematical induction, Formula for n candidates
  • 37. 1. Think about the condition “never less than” instead of “always more than.” Development 2. What if we suppose that the ballots of the 3 rd candidate don’t relate to anyone else?
  • 38.
  • 39. Application In Cryptography Define the plaintext (code) used to send the data Increases the security of the system.
  • 40. Reference Chen Chuan-Chong and Koh Khee-Meng, Principles and Techniques in Combinatorics , World Scientific, 3rd ed., 1999. Marc Renault, Four Proofs of the Ballot Theorem, U.S.A., 2007. Michael L. GARGANO, Lorraine L. LURIE Louis V. QUINTAS, and Eric M. WAHL, The Ballot Problem, U.S.A.,2005. Miklos Bona, Unimodality, Introduction to Enumerative Combinatorics, McGrawHill, 2007. Sriram V. Pemmaraju, Steven S. Skienay, A System for Exploring Combinatorics and Graph Theory in Mathematica, U.S.A., 2004.