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Simple Nature - Light and Matter

Simple Nature - Light and Matter

Simple Nature - Light and Matter

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has ever succeeded in detecting differences among atoms. There isno way for an atom to be changed by the experiences it has in itslifetime.Addition of probabilitiesThe law of independent probabilities tells us to use multiplicationto calculate the probability that both A <strong>and</strong> B will happen,assuming the probabilities are independent. What about the probabilityof an “or” rather than an “<strong>and</strong>”? If two events A <strong>and</strong> Bare mutually exclusive, then the probability of one or the other occurringis the sum P A + P B . For instance, a bowler might have a30% chance of getting a strike (knocking down all ten pins) <strong>and</strong> a20% chance of knocking down nine of them. The bowler’s chance ofknocking down either nine pins or ten pins is therefore 50%.It does not make sense to add probabilities of things that arenot mutually exclusive, i.e., that could both happen. Say I have a90% chance of eating lunch on any given day, <strong>and</strong> a 90% chance ofeating dinner. The probability that I will eat either lunch or dinneris not 180%.NormalizationIf I spin a globe <strong>and</strong> r<strong>and</strong>omly pick a point on it, I have about a70% chance of picking a point that’s in an ocean <strong>and</strong> a 30% chanceof picking a point on l<strong>and</strong>. The probability of picking either wateror l<strong>and</strong> is 70% + 30% = 100%. Water <strong>and</strong> l<strong>and</strong> are mutuallyexclusive, <strong>and</strong> there are no other possibilities, so the probabilitieshad to add up to 100%. It works the same if there are more thantwo possibilities — if you can classify all possible outcomes into alist of mutually exclusive results, then all the probabilities have toadd up to 1, or 100%. This property of probabilities is known asnormalization.AveragesAnother way of dealing with r<strong>and</strong>omness is to take averages.The casino knows that in the long run, the number of times you winwill approximately equal the number of times you play multipliedby the probability of winning. In the slot-machine game describedon page 823, where the probability of winning is 0.001, if you spenda week playing, <strong>and</strong> pay $2500 to play 10,000 times, you are likelyto win about 10 times (10, 000 × 0.001 = 10), <strong>and</strong> collect $1000. Onthe average, the casino will make a profit of $1500 from you. Thisis an example of the following rule.Rule for Calculating AveragesIf you conduct N identical, statistically independent trials,<strong>and</strong> the probability of success in each trial is P , then on theaverage, the total number of successful trials will be NP . If Nis large enough, the relative error in this estimate will becomeb / Normalization: the probabilityof picking l<strong>and</strong> plus theprobability of picking water addsup to 1.Section 13.1 Rules of R<strong>and</strong>omness 825

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