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Flashcards

Chapter 6: Probability

Erin Vales Inglês 20 flashcards

Chapter 6: Probability

Flashcards do conjunto (20)

  1. 1Probabilitythe proportion of times that a certain event is expected to occur
    the study of randomness and uncertainty
  2. 2Sample space Sthe set of all possible outcomes of an experiment
  3. 3Eventa subset of S or a collection of outcomes of an experiment
    each outcome is a simple event
  4. 4Probability Rule AAny probability is a number between 0 and 1
  5. 5Probability Rule BAll possible outcomes together must have probability
  6. 6Probability Rule CThe probability that an event does not occur is 1 minus the probability that the event does occur
    P(A') = 1 - P(A)
  7. 7Mutually ExclusiveIf two events have no outcomes in common, that is they both cannot happen simultaneously,
  8. 8Mutually Exclusive EventsThe probability that one or the other of the two mutually exclusive events occur is the sum of their individual probabilities
    P(A or B) = P(A) + P(B)
  9. 9Independent EventsIf two events do not influence each other and if the knowledge about one does not help in the knowledge of the probability of the other, the events are said to be independent of each other
  10. 10Independent Event ProbabilityIf two events are independent, then the probability that they both happen is found by multiplying their individual probabilities
    P(A and B) = P(A) * P(B)
  11. 11Discrete variableIf and only if it takes on a finite number of values or a countably infinite number of values
    - ex. number of students in a class
  12. 12Continuous variablewhen it takes on values which lie on a continuum or an interval of the real line
    - ex. amount of water in a gallon bucket
  13. 13Probability distribution of Discrete Random variableexpressed by a probability mass function (pmf) and a probability histogramProbability distribution of Discrete Random variable
  14. 14ParameterWhen p(x) = P( X = x ) depends on a quantity which can take on various values
  15. 15Rule for PMFIf you have a probability model for a discrete random variable X...
    1. each probability must be a number between 0 and 1
    2. probabilities must add up to 1
    Rule for PMF
  16. 16Expected Value of Discrete Random variablesDef: The long term average value of a random variable.
    The expectation or mean of X is given by
    Expected Value of Discrete Random variables
  17. 17Variance and Standard Deviation of Discrete random variablesVariance and Standard Deviation of Discrete random variables
  18. 18Probability Density Function (pdf)the mathematical model for a continuous random variable X
  19. 19Probability Density Curvethe graph of the probability density function (pdf)
    the curve that smoothes out a histogram
    Probability Density Curve
  20. 20Properties of a Property Density Function (pdf)For any value of a random variable X for which X is defined, f(X) should be non-negative
    The total area under the probability density curve should be 1
    Properties of a Property Density Function (pdf)

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Interpretation and Basic rules
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Erin Vales
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