SlideShare a Scribd company logo
Probability Case Study RohiniGandhotra Susan ForgettRheam Thomas Smith
Probability is a numeric value of the likelihood, or chance, of something happening. Do we have a better chance of this event occurring or do we have a better chance of it not occurring? Generally, we discuss probability as a fraction, a decimal, or a percent (%). Introduction
0 < P < 1 ,[object Object]
Where 1 is an event that is sure to occur
In between, the possibility that an event will occur
The sum of the probabilities of all possible outcomes of an event is one (1).Probability Rules
Classical – probability of success is based on prior knowledge of the process involved. Empirical – the outcomes are based on observed data, not on prior knowledge of a process. Subjective – based on the decision maker’s opinion regarding the chances that an event will occur. 3 Approaches to Probability
Great Air Commuter Service is a small regional airline. Provides commuter service between Boston and New York – three round trips daily (total of six flights per day). Promotional contest awarding a large prize to be run one day per month on each flight.  Case Study Description
The day each month for contest to be run will be selected randomly on the first of each month. On each flight that day, all passengers will write down their birthday (month and day). If any two people on the plane have the same birthday, they will place their names in a hat and one name will be selected to receive the grand prize. Contest Description
Capacity of each flight is a maximum of 40 passengers (plus crew). The Marketing Director believes there is a very low chance of a birthday match, so only a small chance of giving away the large prize. Marketing Director states that the probability for a match will be 40/365 (10.95%) for a full plane and less than that when there are fewer than 40 passengers on board. Other Case Information
Probability Question The owner wants to know: What is the probability of one or more birthday matches on flights of 20, 30, or 40 passengers,?
Is the Marketing Director accurate in her assessment? Let’s test
Independent events are events in which the occurrence of the events will not affect the probability of the occurrence of any of the other events. Example:  The date of my birth has no bearing on your birth date. For independent events, the probability of all of the events occurring is equal to a product of the probabilities of each event occurring: P(A and B) = P(A) * P(B) * … Multiplication Rule for Independent Events
[object Object]
Looked at another way, what is the probability of 20 passengers not sharing a birthday?
20 independent events with each event as a corresponding person not sharing their birthday with any of the previously analyzed people.Calculating the Probability
DISREGARD: ,[object Object]
Twins
Seasonality of births***There are 365 birthdays equally likely Assumptions
Classical Probability: P(A) = the probability of at least two passengers having the same birthday: P(A) =    # of ways for event to occur                Total # of possible outcomes Calculating the Probability
The complement of event A: P(A’) = the probability of there not being any two passengers with the same birthday. Then, because P(A) and P(A’) are the only two possibilities and are also mutually exclusive: P(A’) = 1 – P(A) Calculating the Probability
P(1) = for one person, there are 365 distinct birthdays P(1) = 365            365 P(2) = for two people, there are 364 different ways that the second could have a birthday without matching the first: P(2) = 364            365 20 Passenger Probability Calculation
P(3) = if person 3 is born on any of the 363 days of the year other than the birthdays of people 1 and 2, person 3 will not share their birthday. P(3) = 363            365 20 Passenger Probability Calculation
Calculating for all 20 passengers: P(A’) = 365 * 364 * 363 * 362 * …*346  = .588528              365    365    365    365          365 Therefore, the probability of at least two passengers having the same birthday is: P(A) = 1 - .588528  or  41.15% 20 Passenger Probability Calculation
30 Passengers: P(A’) = 365 * 364 * 363 * 362 * …*336  = .293665              365    365    365    365          365 P(A) = 1 - .293665          = 70.63% 30 Passenger Calculation

More Related Content

What's hot

Management accounting
Management accountingManagement accounting
Management accounting
pooja sonakiya
 
Operation research and its application
Operation research and its applicationOperation research and its application
Operation research and its application
ArunNair272
 
Statistics lecture 12 (chapter 12)
Statistics lecture 12 (chapter 12)Statistics lecture 12 (chapter 12)
Statistics lecture 12 (chapter 12)
jillmitchell8778
 
operation research notes
operation research notesoperation research notes
operation research notes
Renu Thakur
 
Business statistics
Business statisticsBusiness statistics
Business statistics
Homework Guru
 
Linear regression theory
Linear regression theoryLinear regression theory
Linear regression theory
Saurav Mukherjee
 
Use of statistics in real life
Use of statistics in real lifeUse of statistics in real life
Use of statistics in real life
Harsh Rajput
 
Covariance and correlation
Covariance and correlationCovariance and correlation
Covariance and correlation
Rashid Hussain
 
Moving average method maths ppt
Moving average method maths pptMoving average method maths ppt
Moving average method maths ppt
Abhishek Mahto
 
Regression Analysis
Regression AnalysisRegression Analysis
Regression Analysis
ASAD ALI
 
Regression &amp; correlation coefficient
Regression &amp; correlation coefficientRegression &amp; correlation coefficient
Regression &amp; correlation coefficient
MuhamamdZiaSamad
 
Chap18 statistical decision theory
Chap18 statistical decision theoryChap18 statistical decision theory
Chap18 statistical decision theory
Judianto Nugroho
 
Consumption hypotheses
Consumption hypothesesConsumption hypotheses
Consumption hypotheses
Prasoon Agarwal
 
Simple linear regression (final)
Simple linear regression (final)Simple linear regression (final)
Simple linear regression (final)
Harsh Upadhyay
 
Correlation analysis ppt
Correlation analysis pptCorrelation analysis ppt
Correlation analysis ppt
David Jaison
 
Probability concept and Probability distribution
Probability concept and Probability distributionProbability concept and Probability distribution
Probability concept and Probability distribution
Southern Range, Berhampur, Odisha
 
Index Number
Index NumberIndex Number
Index Number
deepakashwani
 
Econometrics lecture 1st
Econometrics lecture 1stEconometrics lecture 1st
Econometrics lecture 1st
Ishaq Ahmad
 
Econometrics chapter 8
Econometrics chapter 8Econometrics chapter 8
Econometrics chapter 8
Sehrish Chaudary
 
Time series
Time seriesTime series
Time series
Hasnain Baber
 

What's hot (20)

Management accounting
Management accountingManagement accounting
Management accounting
 
Operation research and its application
Operation research and its applicationOperation research and its application
Operation research and its application
 
Statistics lecture 12 (chapter 12)
Statistics lecture 12 (chapter 12)Statistics lecture 12 (chapter 12)
Statistics lecture 12 (chapter 12)
 
operation research notes
operation research notesoperation research notes
operation research notes
 
Business statistics
Business statisticsBusiness statistics
Business statistics
 
Linear regression theory
Linear regression theoryLinear regression theory
Linear regression theory
 
Use of statistics in real life
Use of statistics in real lifeUse of statistics in real life
Use of statistics in real life
 
Covariance and correlation
Covariance and correlationCovariance and correlation
Covariance and correlation
 
Moving average method maths ppt
Moving average method maths pptMoving average method maths ppt
Moving average method maths ppt
 
Regression Analysis
Regression AnalysisRegression Analysis
Regression Analysis
 
Regression &amp; correlation coefficient
Regression &amp; correlation coefficientRegression &amp; correlation coefficient
Regression &amp; correlation coefficient
 
Chap18 statistical decision theory
Chap18 statistical decision theoryChap18 statistical decision theory
Chap18 statistical decision theory
 
Consumption hypotheses
Consumption hypothesesConsumption hypotheses
Consumption hypotheses
 
Simple linear regression (final)
Simple linear regression (final)Simple linear regression (final)
Simple linear regression (final)
 
Correlation analysis ppt
Correlation analysis pptCorrelation analysis ppt
Correlation analysis ppt
 
Probability concept and Probability distribution
Probability concept and Probability distributionProbability concept and Probability distribution
Probability concept and Probability distribution
 
Index Number
Index NumberIndex Number
Index Number
 
Econometrics lecture 1st
Econometrics lecture 1stEconometrics lecture 1st
Econometrics lecture 1st
 
Econometrics chapter 8
Econometrics chapter 8Econometrics chapter 8
Econometrics chapter 8
 
Time series
Time seriesTime series
Time series
 

Similar to Probability Case Study Rheam, Smith, Gandhotra

Probability in action
Probability in actionProbability in action
Probability in action
in_sandeep
 
group1-151014013653-lva1-app6891.pdf
group1-151014013653-lva1-app6891.pdfgroup1-151014013653-lva1-app6891.pdf
group1-151014013653-lva1-app6891.pdf
VenkateshPandiri4
 
introduction to probability
introduction to probabilityintroduction to probability
introduction to probability
lovemucheca
 
Probability Theory
Probability Theory Probability Theory
Probability Theory
Anthony J. Evans
 
Chapter 05
Chapter 05Chapter 05
Chapter 05
bmcfad01
 
Statistics assignment 5
Statistics assignment 5Statistics assignment 5
Statistics assignment 5
Ishaq Ahmed
 
Chapter 05
Chapter 05 Chapter 05
Chapter 05
Tuul Tuul
 
Probability theory good
Probability theory goodProbability theory good
Probability theory good
Zahida Pervaiz
 
3.2 probablity
3.2 probablity3.2 probablity
Lesson 5.ppt
Lesson 5.pptLesson 5.ppt
Lesson 5.ppt
OkianWarner
 
Presentation1 probability
Presentation1 probabilityPresentation1 probability
Presentation1 probability
Dilveer Pahwa
 
03 Conditional
03 Conditional03 Conditional
03 Conditional
Hadley Wickham
 
Tp4 probability
Tp4 probabilityTp4 probability
Tp4 probability
Ishara .S. Saranapala
 
Probabilities distributions
Probabilities distributionsProbabilities distributions
Probabilities distributions
Learnbay Datascience
 
Chapter 4
Chapter 4Chapter 4
Chapter 4
guest3720ca
 
Chapter 4
Chapter 4Chapter 4
Chapter 4
Rose Jenkins
 
03+probability+distributions.ppt
03+probability+distributions.ppt03+probability+distributions.ppt
03+probability+distributions.ppt
abhinav3874
 
Probablity Theory IVME 12022013-1.ppt
Probablity Theory IVME 12022013-1.pptProbablity Theory IVME 12022013-1.ppt
Probablity Theory IVME 12022013-1.ppt
k224802
 
lesson4-intrduction to probability grade10
lesson4-intrduction to probability grade10lesson4-intrduction to probability grade10
lesson4-intrduction to probability grade10
CharlesIanVArnado
 

Similar to Probability Case Study Rheam, Smith, Gandhotra (19)

Probability in action
Probability in actionProbability in action
Probability in action
 
group1-151014013653-lva1-app6891.pdf
group1-151014013653-lva1-app6891.pdfgroup1-151014013653-lva1-app6891.pdf
group1-151014013653-lva1-app6891.pdf
 
introduction to probability
introduction to probabilityintroduction to probability
introduction to probability
 
Probability Theory
Probability Theory Probability Theory
Probability Theory
 
Chapter 05
Chapter 05Chapter 05
Chapter 05
 
Statistics assignment 5
Statistics assignment 5Statistics assignment 5
Statistics assignment 5
 
Chapter 05
Chapter 05 Chapter 05
Chapter 05
 
Probability theory good
Probability theory goodProbability theory good
Probability theory good
 
3.2 probablity
3.2 probablity3.2 probablity
3.2 probablity
 
Lesson 5.ppt
Lesson 5.pptLesson 5.ppt
Lesson 5.ppt
 
Presentation1 probability
Presentation1 probabilityPresentation1 probability
Presentation1 probability
 
03 Conditional
03 Conditional03 Conditional
03 Conditional
 
Tp4 probability
Tp4 probabilityTp4 probability
Tp4 probability
 
Probabilities distributions
Probabilities distributionsProbabilities distributions
Probabilities distributions
 
Chapter 4
Chapter 4Chapter 4
Chapter 4
 
Chapter 4
Chapter 4Chapter 4
Chapter 4
 
03+probability+distributions.ppt
03+probability+distributions.ppt03+probability+distributions.ppt
03+probability+distributions.ppt
 
Probablity Theory IVME 12022013-1.ppt
Probablity Theory IVME 12022013-1.pptProbablity Theory IVME 12022013-1.ppt
Probablity Theory IVME 12022013-1.ppt
 
lesson4-intrduction to probability grade10
lesson4-intrduction to probability grade10lesson4-intrduction to probability grade10
lesson4-intrduction to probability grade10
 

Recently uploaded

Anny Serafina Love - Letter of Recommendation by Kellen Harkins, MS.
Anny Serafina Love - Letter of Recommendation by Kellen Harkins, MS.Anny Serafina Love - Letter of Recommendation by Kellen Harkins, MS.
Anny Serafina Love - Letter of Recommendation by Kellen Harkins, MS.
AnnySerafinaLove
 
Industrial Tech SW: Category Renewal and Creation
Industrial Tech SW:  Category Renewal and CreationIndustrial Tech SW:  Category Renewal and Creation
Industrial Tech SW: Category Renewal and Creation
Christian Dahlen
 
Evgen Osmak: Methods of key project parameters estimation: from the shaman-in...
Evgen Osmak: Methods of key project parameters estimation: from the shaman-in...Evgen Osmak: Methods of key project parameters estimation: from the shaman-in...
Evgen Osmak: Methods of key project parameters estimation: from the shaman-in...
Lviv Startup Club
 
BeMetals Investor Presentation_June 1, 2024.pdf
BeMetals Investor Presentation_June 1, 2024.pdfBeMetals Investor Presentation_June 1, 2024.pdf
BeMetals Investor Presentation_June 1, 2024.pdf
DerekIwanaka1
 
Dpboss Matka Guessing Satta Matta Matka Kalyan Chart Satta Matka
Dpboss Matka Guessing Satta Matta Matka Kalyan Chart Satta MatkaDpboss Matka Guessing Satta Matta Matka Kalyan Chart Satta Matka
Dpboss Matka Guessing Satta Matta Matka Kalyan Chart Satta Matka
➒➌➎➏➑➐➋➑➐➐Dpboss Matka Guessing Satta Matka Kalyan Chart Indian Matka
 
Chapter 7 Final business management sciences .ppt
Chapter 7 Final business management sciences .pptChapter 7 Final business management sciences .ppt
Chapter 7 Final business management sciences .ppt
ssuser567e2d
 
Creative Web Design Company in Singapore
Creative Web Design Company in SingaporeCreative Web Design Company in Singapore
Creative Web Design Company in Singapore
techboxsqauremedia
 
-- June 2024 is National Volunteer Month --
-- June 2024 is National Volunteer Month ---- June 2024 is National Volunteer Month --
-- June 2024 is National Volunteer Month --
NZSG
 
Part 2 Deep Dive: Navigating the 2024 Slowdown
Part 2 Deep Dive: Navigating the 2024 SlowdownPart 2 Deep Dive: Navigating the 2024 Slowdown
Part 2 Deep Dive: Navigating the 2024 Slowdown
jeffkluth1
 
ModelingMarketingStrategiesMKS.CollumbiaUniversitypdf
ModelingMarketingStrategiesMKS.CollumbiaUniversitypdfModelingMarketingStrategiesMKS.CollumbiaUniversitypdf
ModelingMarketingStrategiesMKS.CollumbiaUniversitypdf
fisherameliaisabella
 
Creative Web Design Company in Singapore
Creative Web Design Company in SingaporeCreative Web Design Company in Singapore
Creative Web Design Company in Singapore
techboxsqauremedia
 
Lundin Gold Corporate Presentation - June 2024
Lundin Gold Corporate Presentation - June 2024Lundin Gold Corporate Presentation - June 2024
Lundin Gold Corporate Presentation - June 2024
Adnet Communications
 
Understanding User Needs and Satisfying Them
Understanding User Needs and Satisfying ThemUnderstanding User Needs and Satisfying Them
Understanding User Needs and Satisfying Them
Aggregage
 
Building Your Employer Brand with Social Media
Building Your Employer Brand with Social MediaBuilding Your Employer Brand with Social Media
Building Your Employer Brand with Social Media
LuanWise
 
Hamster Kombat' Telegram Game Surpasses 100 Million Players—Token Release Sch...
Hamster Kombat' Telegram Game Surpasses 100 Million Players—Token Release Sch...Hamster Kombat' Telegram Game Surpasses 100 Million Players—Token Release Sch...
Hamster Kombat' Telegram Game Surpasses 100 Million Players—Token Release Sch...
SOFTTECHHUB
 
Unveiling the Dynamic Personalities, Key Dates, and Horoscope Insights: Gemin...
Unveiling the Dynamic Personalities, Key Dates, and Horoscope Insights: Gemin...Unveiling the Dynamic Personalities, Key Dates, and Horoscope Insights: Gemin...
Unveiling the Dynamic Personalities, Key Dates, and Horoscope Insights: Gemin...
my Pandit
 
buy old yahoo accounts buy yahoo accounts
buy old yahoo accounts buy yahoo accountsbuy old yahoo accounts buy yahoo accounts
buy old yahoo accounts buy yahoo accounts
Susan Laney
 
3 Simple Steps To Buy Verified Payoneer Account In 2024
3 Simple Steps To Buy Verified Payoneer Account In 20243 Simple Steps To Buy Verified Payoneer Account In 2024
3 Simple Steps To Buy Verified Payoneer Account In 2024
SEOSMMEARTH
 
ikea_woodgreen_petscharity_cat-alogue_digital.pdf
ikea_woodgreen_petscharity_cat-alogue_digital.pdfikea_woodgreen_petscharity_cat-alogue_digital.pdf
ikea_woodgreen_petscharity_cat-alogue_digital.pdf
agatadrynko
 
LA HUG - Video Testimonials with Chynna Morgan - June 2024
LA HUG - Video Testimonials with Chynna Morgan - June 2024LA HUG - Video Testimonials with Chynna Morgan - June 2024
LA HUG - Video Testimonials with Chynna Morgan - June 2024
Lital Barkan
 

Recently uploaded (20)

Anny Serafina Love - Letter of Recommendation by Kellen Harkins, MS.
Anny Serafina Love - Letter of Recommendation by Kellen Harkins, MS.Anny Serafina Love - Letter of Recommendation by Kellen Harkins, MS.
Anny Serafina Love - Letter of Recommendation by Kellen Harkins, MS.
 
Industrial Tech SW: Category Renewal and Creation
Industrial Tech SW:  Category Renewal and CreationIndustrial Tech SW:  Category Renewal and Creation
Industrial Tech SW: Category Renewal and Creation
 
Evgen Osmak: Methods of key project parameters estimation: from the shaman-in...
Evgen Osmak: Methods of key project parameters estimation: from the shaman-in...Evgen Osmak: Methods of key project parameters estimation: from the shaman-in...
Evgen Osmak: Methods of key project parameters estimation: from the shaman-in...
 
BeMetals Investor Presentation_June 1, 2024.pdf
BeMetals Investor Presentation_June 1, 2024.pdfBeMetals Investor Presentation_June 1, 2024.pdf
BeMetals Investor Presentation_June 1, 2024.pdf
 
Dpboss Matka Guessing Satta Matta Matka Kalyan Chart Satta Matka
Dpboss Matka Guessing Satta Matta Matka Kalyan Chart Satta MatkaDpboss Matka Guessing Satta Matta Matka Kalyan Chart Satta Matka
Dpboss Matka Guessing Satta Matta Matka Kalyan Chart Satta Matka
 
Chapter 7 Final business management sciences .ppt
Chapter 7 Final business management sciences .pptChapter 7 Final business management sciences .ppt
Chapter 7 Final business management sciences .ppt
 
Creative Web Design Company in Singapore
Creative Web Design Company in SingaporeCreative Web Design Company in Singapore
Creative Web Design Company in Singapore
 
-- June 2024 is National Volunteer Month --
-- June 2024 is National Volunteer Month ---- June 2024 is National Volunteer Month --
-- June 2024 is National Volunteer Month --
 
Part 2 Deep Dive: Navigating the 2024 Slowdown
Part 2 Deep Dive: Navigating the 2024 SlowdownPart 2 Deep Dive: Navigating the 2024 Slowdown
Part 2 Deep Dive: Navigating the 2024 Slowdown
 
ModelingMarketingStrategiesMKS.CollumbiaUniversitypdf
ModelingMarketingStrategiesMKS.CollumbiaUniversitypdfModelingMarketingStrategiesMKS.CollumbiaUniversitypdf
ModelingMarketingStrategiesMKS.CollumbiaUniversitypdf
 
Creative Web Design Company in Singapore
Creative Web Design Company in SingaporeCreative Web Design Company in Singapore
Creative Web Design Company in Singapore
 
Lundin Gold Corporate Presentation - June 2024
Lundin Gold Corporate Presentation - June 2024Lundin Gold Corporate Presentation - June 2024
Lundin Gold Corporate Presentation - June 2024
 
Understanding User Needs and Satisfying Them
Understanding User Needs and Satisfying ThemUnderstanding User Needs and Satisfying Them
Understanding User Needs and Satisfying Them
 
Building Your Employer Brand with Social Media
Building Your Employer Brand with Social MediaBuilding Your Employer Brand with Social Media
Building Your Employer Brand with Social Media
 
Hamster Kombat' Telegram Game Surpasses 100 Million Players—Token Release Sch...
Hamster Kombat' Telegram Game Surpasses 100 Million Players—Token Release Sch...Hamster Kombat' Telegram Game Surpasses 100 Million Players—Token Release Sch...
Hamster Kombat' Telegram Game Surpasses 100 Million Players—Token Release Sch...
 
Unveiling the Dynamic Personalities, Key Dates, and Horoscope Insights: Gemin...
Unveiling the Dynamic Personalities, Key Dates, and Horoscope Insights: Gemin...Unveiling the Dynamic Personalities, Key Dates, and Horoscope Insights: Gemin...
Unveiling the Dynamic Personalities, Key Dates, and Horoscope Insights: Gemin...
 
buy old yahoo accounts buy yahoo accounts
buy old yahoo accounts buy yahoo accountsbuy old yahoo accounts buy yahoo accounts
buy old yahoo accounts buy yahoo accounts
 
3 Simple Steps To Buy Verified Payoneer Account In 2024
3 Simple Steps To Buy Verified Payoneer Account In 20243 Simple Steps To Buy Verified Payoneer Account In 2024
3 Simple Steps To Buy Verified Payoneer Account In 2024
 
ikea_woodgreen_petscharity_cat-alogue_digital.pdf
ikea_woodgreen_petscharity_cat-alogue_digital.pdfikea_woodgreen_petscharity_cat-alogue_digital.pdf
ikea_woodgreen_petscharity_cat-alogue_digital.pdf
 
LA HUG - Video Testimonials with Chynna Morgan - June 2024
LA HUG - Video Testimonials with Chynna Morgan - June 2024LA HUG - Video Testimonials with Chynna Morgan - June 2024
LA HUG - Video Testimonials with Chynna Morgan - June 2024
 

Probability Case Study Rheam, Smith, Gandhotra

  • 1. Probability Case Study RohiniGandhotra Susan ForgettRheam Thomas Smith
  • 2. Probability is a numeric value of the likelihood, or chance, of something happening. Do we have a better chance of this event occurring or do we have a better chance of it not occurring? Generally, we discuss probability as a fraction, a decimal, or a percent (%). Introduction
  • 3.
  • 4. Where 1 is an event that is sure to occur
  • 5. In between, the possibility that an event will occur
  • 6. The sum of the probabilities of all possible outcomes of an event is one (1).Probability Rules
  • 7. Classical – probability of success is based on prior knowledge of the process involved. Empirical – the outcomes are based on observed data, not on prior knowledge of a process. Subjective – based on the decision maker’s opinion regarding the chances that an event will occur. 3 Approaches to Probability
  • 8. Great Air Commuter Service is a small regional airline. Provides commuter service between Boston and New York – three round trips daily (total of six flights per day). Promotional contest awarding a large prize to be run one day per month on each flight. Case Study Description
  • 9. The day each month for contest to be run will be selected randomly on the first of each month. On each flight that day, all passengers will write down their birthday (month and day). If any two people on the plane have the same birthday, they will place their names in a hat and one name will be selected to receive the grand prize. Contest Description
  • 10. Capacity of each flight is a maximum of 40 passengers (plus crew). The Marketing Director believes there is a very low chance of a birthday match, so only a small chance of giving away the large prize. Marketing Director states that the probability for a match will be 40/365 (10.95%) for a full plane and less than that when there are fewer than 40 passengers on board. Other Case Information
  • 11. Probability Question The owner wants to know: What is the probability of one or more birthday matches on flights of 20, 30, or 40 passengers,?
  • 12. Is the Marketing Director accurate in her assessment? Let’s test
  • 13. Independent events are events in which the occurrence of the events will not affect the probability of the occurrence of any of the other events. Example: The date of my birth has no bearing on your birth date. For independent events, the probability of all of the events occurring is equal to a product of the probabilities of each event occurring: P(A and B) = P(A) * P(B) * … Multiplication Rule for Independent Events
  • 14.
  • 15. Looked at another way, what is the probability of 20 passengers not sharing a birthday?
  • 16. 20 independent events with each event as a corresponding person not sharing their birthday with any of the previously analyzed people.Calculating the Probability
  • 17.
  • 18. Twins
  • 19. Seasonality of births***There are 365 birthdays equally likely Assumptions
  • 20. Classical Probability: P(A) = the probability of at least two passengers having the same birthday: P(A) = # of ways for event to occur Total # of possible outcomes Calculating the Probability
  • 21. The complement of event A: P(A’) = the probability of there not being any two passengers with the same birthday. Then, because P(A) and P(A’) are the only two possibilities and are also mutually exclusive: P(A’) = 1 – P(A) Calculating the Probability
  • 22. P(1) = for one person, there are 365 distinct birthdays P(1) = 365 365 P(2) = for two people, there are 364 different ways that the second could have a birthday without matching the first: P(2) = 364 365 20 Passenger Probability Calculation
  • 23. P(3) = if person 3 is born on any of the 363 days of the year other than the birthdays of people 1 and 2, person 3 will not share their birthday. P(3) = 363 365 20 Passenger Probability Calculation
  • 24. Calculating for all 20 passengers: P(A’) = 365 * 364 * 363 * 362 * …*346 = .588528 365 365 365 365 365 Therefore, the probability of at least two passengers having the same birthday is: P(A) = 1 - .588528 or 41.15% 20 Passenger Probability Calculation
  • 25. 30 Passengers: P(A’) = 365 * 364 * 363 * 362 * …*336 = .293665 365 365 365 365 365 P(A) = 1 - .293665 = 70.63% 30 Passenger Calculation
  • 26. 40 Passengers: P(A’) = 365 * 364 * 363 * 362 * …*326 = .108760 365 365 365 365 365 P(A) = 1 - .108760 = 89.12% 40 Passenger Calculation
  • 27. 20 Passengers = 41.15% 30 Passengers = 70.63% 40 Passengers = 89.12 % Seems implausible, doesn’t it? Birthday Probability Summary
  • 28. Some of the terms people use for probability are: Chance Likelihood The chance that any one person in this room shares my birthday is much smaller: 1 – {(364/365) 25 times} or 6.7%. Our probability calculation reflects that it is likely that there are some birthday matches among the other people in the group, not matching just to me. Understanding Probability
  • 29.
  • 30. Joanne Woodward and Elizabeth Taylor (Feb 27)
  • 31. Barbra Streisand and Shirley MacLaine (April 24)http://en.wikipedia.org/wiki/Birthday_problem Tests of this probability:
  • 32. With six flights daily (carrying the same number of passengers: 20, 30, and 40), what are the chances that Great Air Commuter Service will end up awarding two or more major prizes during a given month? Awarding Prizes
  • 33. Consider the number of flights on the one day per month the contest is run (3 round trips, 6 flights total) Multiply by the probability of a birthday match assuming group size (20, 30, and 40 passenger possibilities). 6 x .4115 = 2.47 prizes/month for 20 passenger flights 6 x .7063 = 4.24 prizes/month for 30 passenger flights 6 x .8912 = 5.35 prizes/month for 40 passenger flights Awarding Prizes
  • 34.
  • 35. If I make everything unpredictable, human beings will have no motive to do anything as there is no rational basis for any decision.
  • 36. I must therefore create a mixture of two.[from E. F. Schumacher] LORD Final Thought on Probability