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APUSH STUDY notes for unit 5 of the class.
Typology: Study notes
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Probability
The probability of any outcome of a chance process is a number between 0 and 1 that describes the proportion of times the outcome would occur in a very long series of repetitions.
Simulation
The imitation of chance behavior, based on a model that accurately reflects the situation, is called a simulation.
Performing of a Simulation – The 4-Step Process
1. State : Ask a question of interest about some chance process. 2. Plan : Describe how to use a chance device to imitate one repetition of the process. Tell what you will record at the end of each repetition. 3. Do : Perform many repetitions of the simulation. 4. Conclude : Use the results of your simulation to answer the question of interest.
Sample Space
The sample space S of a chance process is the set of all possible outcomes.
Probability Models
Descriptions of chance behavior contain two parts:
A probability model is a description of some chance process that consists of two parts:
For example: When a fair 6-sided die is rolled, the Sample Space is S = {1, 2, 3, ,4,5, 6}. The probability for a fair die would include the probabilities of these outcomes, which are all the same.
Outcome 1 2 3 4 5 6 Probability 1/6 1/6 1/6 1/6 1/6 1/
Event An event is any collection of outcomes from some chance process. That is, an event is a subset of the sample space. Events are usually designated by capital letters, like A, B, C , and so on.
For example : For the probability model above we might define event A = die roll is odd. The elements of the sample space S that fits this event are {1, 3, 5}. The probability of the event A, written as P(A) is the 3/6 or ½. So we would write P(A) = 0.5, in decimal form.
The Basic Rules of Probability
totalnumberofoutcomesinsamplespace
numberofoutcomescorrespondingtoevent ( )
Mutually Exclusive Events Two events A and B are mutually exclusive (or disjoint ) if they have no outcomes in common and so can never occur together—that is, if P ( A and B ) = 0. Alternate notation: 𝑷(𝑨 ∩ 𝑩).
For example : Using a deck of playing cards and drawing a card at random, the events A = card is a King, and B = card is a Queen are mutually exclusive because a single card cannot be both a King and a Queen. Thus we can calculate the probability of A or B as the sum of their individual probabilities - P(A or B) = P(A) + P(B).
General Addition Rule If A and B are any two events resulting from some chance process, then P ( A or B ) = P ( A ) + P ( B ) – P ( A and B )
Venn Diagrams and Probability
The complement Ac^ contains exactly the outcomes that are not in A.
The events A and B are mutually exclusive (disjoint) because they do not overlap. That is, they have no outcomes in common.
The intersection of events A and B ( A ∩ B ) is the set of all outcomes in both events A and B.
The union of events A and B ( A ∪ B ) is the set of all outcomes in either event A or B.