Summary

These notes cover basic concepts of probability. Topics include probability definitions, set operations, mutually exclusive events, and independence. Exemplars are provided throughout the document.

Full Transcript

Basic probability probability (P) = favorable outcome total outcome : steps i s 1) identify total # of outcomes 2) identify # of favorable...

Basic probability probability (P) = favorable outcome total outcome : steps i s 1) identify total # of outcomes 2) identify # of favorable outcomes 3) use probability formula 4) simplify fraction Ex I. A deck of 52 cards is shuffled + one card is drawn & random. What is the probability that card is a heart decks piheart) = 13 heart 52 total curds Basic Set Operation P(AUB) = P(A) + P(B) - P(A1B) SetA SetB union (U) : probability that element A or B or both ↳ set A (only ↳ Set B (only ↑ ↳ both set A & B (overlap Set AUB intersection (1) : probability that element is in both A and B compliment : probability that element is not in a given set steps : ~ 1) identify P(A) , PCB) , and PLANB) 2) convert given # into probabilities 3) plug into formula EX.2 In a class of 100 students , 60 are enrolled in Mathematics (Set A) , 50 in Physics (Set B) , and 30 in both courses What. is the probability that a rand- only selected student is enrolled in Mathematics or physics P(AUB) = P(A) + P(B) P(AB) - P(A) = 0 6. P(AUB) = 0 6. + 0 5. - 0 3. = 0 8. p(B) = 0 5. P(AnB) = 0 3. Mutually Exclusive Events events A & B are mutually exclusive if AB = 0 ↳ cannot happena same time P(AUB) P(A) + P(B) = Ex 3. Suppose 2 events A & B are mutually exclusive. P(A) = 0 3. and PCB) = 0 4.. What is the probability of AUB ? P(A1B) = 0 P(AUB) P(A) + P(B) = = 0 3+0 4... = 0. 7 Independence events A & B are independent ; the occurrence of one does not effect the probability of other P(AB) P(A) X P(B)= Total Probability Rule call the probability of an even , PCD)-broken dwn by diff condition. ↳ involves mutually exclusive events conditional probability conditional probability of D of D Boccurs given that A occurs given that - & x = PETA)XA) + P(D(B) X P(B) u probability probability probability of event D that event A of event B occurring occures occurring Conditional Probability P(AIB) P(ANB) = or P(BIA)P(A) P(B) P(B) probability of event occurring given that another event has alr occurred. PCAIB) probability of A given B PLANB) probability both A & B occure P(B) probability that B occurs * this is only defined when P(B) > O meaning event B must have a non-zero probability Counting Questions (Combinatorics) asked to count # of ways certain events or arrangements can occur ↳ 4 diff types : 1. permutation : arrangement order matters P(n r) n! , = (n-r) ! 2. Combinations : order does not matter ((n , r)= n ! r! (n r) ! -. factorial 3 : (n ! ) involve multiplying integers up to n! 4. multiplication principle : if , event occurs in m ways a another event both event occur is occurs n ways , than totalIt of ways mxn Random variable cumulative distribution function (CDF) : probability that random variable will take a value less than or equal to a certain value E(X) =) cumulative probability random variable X probability takes on a value less than up to X or equal to Discrete random variable : finite numbers/countable # Of possible outcomes listed # of sum of probabilities of all outcomes less than or equal to %. If X is discrete random CDF is : probability that random variable X takes place less than or equal to certain value X I F(x) P(XIX) (x xi) = = = random variable Sum of probabilities P(X Xi) = for all Xi add up all values of X that are

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