Probability – Page 1CSCI 1900 – Discrete Structures CSCI 1900 Discrete Structures Probability Reading: Kolman, Section 3.4.

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Presentation transcript:

Probability – Page 1CSCI 1900 – Discrete Structures CSCI 1900 Discrete Structures Probability Reading: Kolman, Section 3.4

Probability – Page 2CSCI 1900 – Discrete Structures Probability Theory There are two types of experiments: –Deterministic – the outcome is always the same –Probabilistic – the outcome could be any of a number of possible outcomes Now that we know how to “count” using the multiplication principle, permutations, and combinations, we can figure out the probability of a certain outcome for probabilistic experiments.

Probability – Page 3CSCI 1900 – Discrete Structures Sample Spaces The set of all possible outcomes of a probabi- listic experiment is called the sample space. Tossing a pair of dice results in one of 7 C 2.

Probability – Page 4CSCI 1900 – Discrete Structures Sample Spaces (continued) The previous slide doesn’t take into account the fact that in all but 6 cases, each pattern could be the result of 2 different rolls

Probability – Page 5CSCI 1900 – Discrete Structures Sample Spaces (continued) When determining the size of the sample space, you need to be sure of the method by which the sample space is created. Rolling dice – duplicates allowed, order matters (multiplication principle) Poker – duplicates not allowed, order doesn’t matter (combinations)

Probability – Page 6CSCI 1900 – Discrete Structures Events An event is a set of outcomes that satisfy a statement (remember that a statement is something that must be true or false). Poker example – a statement about a hand of poker might be that the hand contained four of a kind. Dice example – a statement about a roll of the dice might be that a pair came up or that the sum of the dots equals 7.

Probability – Page 7CSCI 1900 – Discrete Structures Events (continued) The list of all possible outcomes that satisfies an event makes a set. The events for which a roll of dice results in a pair is {(1,1), (2,2), (3,3), (4,4), (5,5), (6,6)}. The events for which a roll of dice results in a sum of 7 is {(1,6), (2,5), (3,4), (4,3), (5,2), (6,1)}.

Probability – Page 8CSCI 1900 – Discrete Structures Events (continued) Since an event is a set, then all of the operations on sets can apply to events. The events for which a roll of a pair of dice is either a pair or the sum equals 7 is {(1,1), (2,2), (3,3), (4,4), (5,5), (6,6), (1,6), (2,5), (3,4), (4,3), (5,2), (6,1)}. The events for which a roll of a pair of dice is a pair and the sum equals 7 is the empty set.

Probability – Page 9CSCI 1900 – Discrete Structures Equally Likely Outcomes Assuming that any outcome is equally likely, i.e., there is no bias towards a particular subset of outcomes, then the probability of any outcome from a sample space with n possible outcomes is: 1/n The probability of an outcome from the event set, E, containing |E| possible outcomes is: |E|/n

Probability – Page 10CSCI 1900 – Discrete Structures Poker Odds Calculation Total possible hands = 52 C 5 = 2,598,960 Royal Straight Flush  4 possible hands Odds are 4 in 2,598,960  1:649,740 Straight Flush  40 possible hands Odds are 40 in 2,598,960  1:64,974 Four Aces  48 possible hands Odds are 48 in 2,598,960  1:54,145 Four of a kind  13 C 1  48 C 1 = 624 hands Odds are 624 in 2,598,960  1:4,165 Full house  13 C 1  4 C 3  12 C 1  4 C 2 = 3,744 Odds are 3,744 in 2,598,960  1:694

Probability – Page 11CSCI 1900 – Discrete Structures In-Class Exercise Is it worth it to play PowerBALL?