SlideServe
Menu
Préférences
© SlideServe · v2026

Understanding Probabilities: Sample Space, Distributions & Principles

lars-salinas avatar
14 diapositives · 244 Views · Nov 13, 2014

Learn how to assign probabilities to outcomes, calculate probabilities for events, apply fundamental principles of probability distributions, and convert odds to probabilities. Includes examples and exercises.

Understanding Probabilities: Sample Space, Distributions & Principles - slide 1
01 / 14Understanding Probabilities: Sample Space, Distributions & Principles
1 / 17

Télécharger la présentation

Understanding Probabilities: Sample Space, Distributions & Principles
Une image / un lien ci-dessous est fourni (tel quel) pour télécharger la présentation

Politique de téléchargement : le contenu du site vous est fourni TEL QUEL pour votre information et votre usage personnel ; il ne peut être vendu, concédé sous licence ni partagé sur d’autres sites sans l’accord de son auteur.Le contenu vous est fourni TEL QUEL, pour votre information et votre usage personnel uniquement. Téléchargez la présentation en cliquant sur ce lien. Lors du téléchargement, si vous ne parvenez pas à télécharger une présentation, l’éditeur a peut-être supprimé le fichier de son serveur.Pendant le téléchargement, si vous ne parvenez pas à obtenir une présentation, le fichier a peut-être été supprimé par l’éditeur.

F I N

Plus de contenu associé

Transcription de la présentation
  1. Chapter 6 Section 3 Assignment of Probabilities

  2. Sample Space and Probabilities • Sample Space : S = { s1 , s2 , s3 , … , sN-1 , sN } where s1 , s2 , s3 , … , sN-1 , sN are all the possible outcomes of the experiment • Each outcome can be assigned a number that represents the probability of an outcome.

  3. Probability Distribution

  4. Fundamental Properties of Probability Distributions • 0 < p1 < 1 0 < p2 < 1 0 < p3 < 1 0 < pN < 1 2. p1 + p2 + p3 + … + pN-1 + pN = 1

  5. Assigning Probabilities • Theoretically • Using Logic and/or Counting Techniques • Best method for assigning probabilities • See Example 1 & 2 on page 273 • Empirically (i.e. Experimentally) • Works only when the observed trial are representative of the sample space. • See Example 3 on pages 273 and 274

  6. Exercise 3 (page 281) • Red die and green die are tossed and the number of the side facing up are observed. • Sample Space: S = { (1,1), (1,2), (1,3), (1,4), (1,5), (1,6), (2,1), (2,2), (2,3), (2,4), (2,5), (2,6), (3,1), (3,2), (3,3), (3,4), (3,5), (3,6), (4,1), (4,2), (4,3), (4,4), (4,5), (4,6), (5,1), (5,2), (5,3), (5,4), (5,5), (5,6), (6,1), (6,2), (6,3), (6,4), (6,5), (6,6) }

  7. Exercise 3 continued • Note that each pair is equally likely to be picked if we randomly select a pair, thus the probability distribution is: OutcomeProbability s1 = (1,1) p1 = 1/36 s2 = (1,2) p2 = 1/36 s3 = (1,3) p3 = 1/36 s36 = (6,6) p36 = 1/36

  8. Addition Principle • Let the event E be defined as E = { s , t , u , … , z } Then Pr( E ) = Pr(s) + Pr(t) + Pr(u) + … + Pr(z)

  9. Exercise 3 Part (a) • Let E = {‘the numbers add up to 8’} • E = { (2,6) , (3,5) , (4,4) , (5,3) , (6,2) } • Find the Pr( E ) • Pr( E ) = Pr( (2,6) ) + Pr( (3,5) ) + Pr( (4,4) ) + Pr( (5,3) ) + Pr( (6,2) ) • Pr( E ) = 1/36 + 1/36 + 1/36 + 1/36 + 1/36 = 5/36  0.1389

  10. Inclusion – Exclusion Principle as Applied to Probabilities • Let E and F be events, then Pr( E  F ) = Pr ( E ) + Pr ( F ) – Pr( E  F ) Venn Diagrams and Probabilities We can use Venn Diagrams and place numbers that represent the probability that the elements in the basic region will occur.

  11. Exercise 17 (page 282) • Let E and F be events. • Pr( E ) = 0.6 , Pr( F ) = 0.5 , and Pr( E  F ) = 0.4 (a) Find Pr( E  F ) (b) Find Pr( E  F)

  12. Odds • When the odds in favor of an event a to b , then the probability of the event can be found by p = a / ( a + b ) • a represents the number of times that the event occurs • b represents the number of times that the event does not occur

  13. Converting an Odds to a Probability • Example: If the odds of a horse to win a race is 1 to 60, then then probability of the horse winning is: a = 1 and b = 60 p = a / (a + b) = 1 / (1 + 60) = 1/61  0.0164

  14. Converting a Probability to an Odds • List the probability as a decimal number • Convert the decimal number to a fraction. • Reduce the fraction (when possible). • Split the value in the denominator to the sum of two values, where the first value in the sum is the value in the numerator. • Get the values of a and b from the resulting fraction.