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### 30 Cards in this Set

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 false positive test incorrectly indicates the presence of a condition when the subject does not actually have that condition false negative test incorrectly indicates that the subject does not have a condition when the subject actually does have that condition true positive test correctly indicates that a condition is present when it really is present true negative test correctly indicates that a condition is not present when it really is not present test sensitivity the probability of a true positive test specificity the probability of true negative positive predictive value probability that the subject is a true positive given that the test yields a positive result negative predictive value probability that the subject is a true negative given the test yields a negative result prevalence proportion of subjects having some condition rare event rule for inferential statistics if, under a given assumption, the probability of a particular observed event is extremely small, we conclude that the assumption is probably not correct event any collection of results or outcomes of a procedure simple event an outcome or an event that cannot be further broken down into simpler components sample space for a procedure consists of all possible simple events, all outcomes that cannot be broken down any further rule one: relative frequency approximation of probability p(A)=number of times A occurred/number of times trial was repeated rule two: classical approach to probability -requires equally likely outcomes P(A)=number of ways A can occur/number of different simple events=s/n rule three:subjective probabilities P(A) is estimated by using knowledge of the relevant circumstances law of large numbers as a procedure is repeated again and again, the relative frequency probability of an event tends to approach the actual probability simulation process that behaves inthe same ways as the procedure itself, so that similar results are produced complement of event A, denoted by A bar, consists ofa ll outcomes in which event A does not occur rounding off probabilities when expressing the value of a probability, either give the exact fraction or decimal or round off the final decimal results to three significant digits compound event any event combining two or more simple events formal addition rule P(A or B)=P(A)+P(B)-P(A and B) intuitive addition rule to find P(A or B), find the sum of the number of ways event A can occur and the number of ways that event B can occur, adding in such a way that every outcome is counted only once. P(A or B) is equal to that sum, divided by the total number of outcomes in the sample space disjoint -mutually exclusive -events A and B cannot occur at the same time rule of complementary events P(A)+P(Abar)=1 P(Abar)=1-P(A) P(A)=1-P(Abar) tree digram picture of the possible outcomes of a procedure, shown as line segments emanating from one starting point independent two events a and b are independent if the occurence of one does nto affect the probability of the occurence of the other dependent if a and b are not independent they are said to be dependent formal multiplication rule P(A and B)=P(A)*P(B/A) intuitive multiplication rule when finding the probability that event A occurs in one trial and event B occurs in the next trial, multiply the probability of event A by the probability of event B, but be sure that the probability of event B takes into account that previous occurence of event A