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Probability Theory: Terms, Definitions, and Concepts, Quizzes of Statistics

Definitions for key terms in probability theory, including random phenomena, cumulative proportion, subjective probability, sample space, event, disjoint events, intersection, union, conditional probability, and independent events. It explains the concepts of these terms and how they relate to each other.

Typology: Quizzes

2011/2012

Uploaded on 02/21/2012

tatertay
tatertay 🇺🇸

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Download Probability Theory: Terms, Definitions, and Concepts and more Quizzes Statistics in PDF only on Docsity! TERM 1 random phenomena DEFINITION 1 outcome is uncertain TERM 2 cumulative proportion DEFINITION 2 the proportion of times a result has occurred out of the total number of trials w/ a short run, the cumulative proportion varies a lot as the number of trials increases, it becomes more predictable and less random TERM 3 subjective probability DEFINITION 3 probability of an outcome is based on your degree of belief that the outcome will occur, based on the available information ("Personal Probability") Bayesian probability is one of the different interpretations of the concept of probability and belongs to the category of evidential probabilities. TERM 4 sample space DEFINITION 4 set of all possible outcomes for a random phenomenon TERM 5 event DEFINITION 5 subset of the sample space TERM 6 disjoint events DEFINITION 6 do not have any outcomes in common; mutually exclusive TERM 7 intersection DEFINITION 7 outcomes in both A and B; both occur P(A and B) = P(A) X P(B) TERM 8 union DEFINITION 8 outcomes in A or B; A occurs or B occurs or both occur P(A or B) = P(A) + P(B) - P(A and B) TERM 9 conditional probability DEFINITION 9 finding the probability of an event when you know that the outcome was in some particular part of the sample space; used to find a probability about a category for one variable when we know the outcome on another variable P(A|B) = P(A and B)/P(B) TERM 10 Independent Events DEFINITION 10 Check: Is P(A|B) = P(A)? Is P(B|A) = P(B)? Is P(A and B) = P(A) X P(B)? If any one of these is true, the others are also true and the events A and B are independent!
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