AP Statistics Probability Flashcards

8340736451	Fundamental Counting Principal	"How many ways?"	0
8340736452	Fundamental Counting Principal	certain procedure (P) can be broken into a number (n) of successive ordered stages - S subscript r = n ways	1
8340736453	permutation	An r-permutation of a set of n elements is an ORDERED selection of r elements from the set of n elements (Hint: If the things being chosen will do (or have done to them) different things, it's a permutation.)	2
8340736454	permutation key words	officers, place, arranged, line up	3
8340736455	permutation formula		4
8340736456	combination	The number of combinations of n elements taken at r at a time; ORDER DOES NOT MATTER (Hint: If the things being chosen are going to do (or have done to them) the same thing, it's a combination)	5
8340736457	combination key words	team, group, commitee	6
8340736458	combination formula		7
8340736459	sample space	the collection of all possible outcomes of a chance experiment (Example: roll a die, S={1, 2, 3, 4, 5, 6}	8
8340736460	event	any collection of outcomes from the sample space (Example: roll prime numbers, E={2,3,5}	9
8340736461	complement	consists of all outcomes that are not in the event (Example: E super c ={1,4,6}	10
8340736462	Union	the event A or B happening and consists of all outcomes that are in at least one of the 2 events (Example: rolling a prime number or even number E= A U B {2, 3, 4,5,6}	11
8340736463	Interesection	the event A and (think "overlap") B happening and consists of all outcomes that are in both events (example: drawing a red card and a 2, E={2 hearts, 2 diamonds}	12
8340736464	Mutually Exclusive (disjointed)	two events that have no outcomes in common (Example: Roll a 2 or a 5 (with one die))	13
8340736465	Venn Diagrams	used to display relationships between events, helpful in calculating probabilities	14
8340736466	probability	denoted by P(Event), =favorable outcomes/total outcomes (Note: this method for calculating probabilities is only appropriate when the outcomes of the sample are equally likely (not weighted))	15
8340736467	experimental probability	the relative frequency at which a chance experiment occurs	16
8340736468	law of large numbers	As the number of repetitions of a chance experiment increase, the difference between relative frequency of occurrence for an event and the true probability approaches zero	17
8340736469	Rule 1	Legitimate Values; For any event (E),, 0<=P(E)<=1	18
8340736470	Rule 2	Sample Space; If S is the sample space, P(S)=1	19
8340736471	Rule 3	Complement; For any event E, P(E) + P(not E) =1	20
8340736472	Rule 4	Addition; If two events M & N are disjoint, P(M or N)=P(M)+P(N) (General) If two events M&N are not disjoint, (i.e. they intersect) P(M or N) = P(M)+P(N)-P(M and N)	21
8340736473	Rule 5	Multiplication; If two events A & B are independent, P(A) * P(B\|A)	22
8340736474	Rule 6	At least one; The probability that at least one outcome happens is one minus the outcome the nonrof it happens P>=1 = P(1-none)	23
8340736475	Rule 7	Conditional Probability; a probability that takes into account a given condition, P(B\|A) =P(A intersection B)/P(A)	24
8340736476	Independent	2 events are independent if knowing that one will occur (or has occurred) does not change the probability that the other occurs; P(B\|A) = P(B); P intersection B=P(A)*P(B); P(A\|not B)=P(A)	25
8340736477	If two events are independent, then the probability that both occur is...	...the product of the probabilities of each event	26
8340736478	If A and B are mutually exclusive (note: P(A)>0 and P(B)>0)...	...then they are dependent events	27
8340736479	Classical Probability versus Relative Frequency	Classical: the calculation of a probability consists of dividing the number of outcomes that make up an event by the sample space Relative Frequency: P(Event) is defined to be the value approached by the relative frequency of occurrence of the event in a very long series of trials of a chance experiment	28