MDM4U – Grade 12 Data Management – Probability Test

Grade 12 – Data Management

Probability

Experimental and Theoretical Probability

  • Probability: is the value between 0 and 1 that describes that likelihood of an occurrence of a certain event.
  • Experimental Probability: making predictions based on a large number of previous results.
  • Theoretical Probability: Make predictions based on a mathematical model.
  • In general, experimental probability will approach theoretical probability as the number of trials increase.
  • Discrete Sample Space: a sample space where you can count the number of outcomes ie. blue balls
  • Continuous Sample Space: decimal numbers with infinite possibilities ie. Time.
  • Event: is the occurrence of a specific outcome in the sample space.

P(A) = n(A) / n(S)

Probability of A is number of outcomes for A over total possibilities

  • P(A’) the probability that event A will not occur.
    • P(A’) = 1 – P(A)

 

Odds

  • Odds: a ratio used to represent a degree of confidence in whether or not an event will occur.
  • Odds In favour: P(A) : P(A’)
    • = n(A) : n(A’)
  • Odds Against: P(A’) : P(A)
    • = n(A’) : n(A)

 

Probability using counting principles

  • Instead of listing out all possibilities, counting principles such as combinations and permutations can be used to calculate all the possibilities of outcome and the possibilities of the event occurrence.
  • Refer to these links for information about counting principles

 

Independent and Dependent Event

  • Two events are independent if the occurrence of one event has no effect on the occurrence of another event.
  • If two events are independent, then P (A n B) = P(A) P(B)
  • Drawing tree diagrams with probability percentages on the branches can be multiplied
    • P(AA) = P(A)*P(A)
  • ie. When drawing disks from a bag, if the disks are replaced, the 2nd draw will be an independent event.
  • ie. When drawing disks from a bag, but the disks are not replaced, the 2nd draw will be a dependent event.

 

Mutually Exclusive Events

  • Two events are mutually exclusive if when one event occurs, the other event cannot occur.
  • If two events are mutually exclusive, then P(A U B) = P(A) + P(B)
  • If two events are not mutually exclusive, then P( A U B) = P(A) + P(B) – P(A U B)
    • ie Probability of picking a KING or a FOUR is a mutually exclusive event.
    • ie Probability of picking a KING or a RED card is non-mutually exclusive. 

 

Conditional Probability

  • The probability that an event will occur given that another compatible event that already occurred.
  • P(A / B) = P(A and B) / P(B)
    • Probability of A given the occurrence of B is equal to the probability of A and B over the probability that B has occurred.
  • ie. Probability of drawing a QUEEN if we know the chosen card is a face card is an example of conditional probability.