Compléter Intro to ProbabilityVersion en ligne Basic teminology of probability par Olena Hawranick 1 outcome event experiment empirical probability In probability , the playing of the game is called an . 2 sample random outcomes experiment space trials The are the possible results of an experiment , and the of an experiment contains every potential outcome that could occur in one trial of the experiment . 3 trial experiment To find a probability , you need a repeatable procedure , or . 4 An A trial event consists of a particular set of outcomes . 5 event outcomes space sample experiment trial event outcomes For a coin - tossing experiment : The is flipping the coin and observing which surface of the coin is visible . The possible are a head or a tail . The would be S = { Head , Tail } . If flipping a coin twice , an might be getting at least one head . This would involve the following set of three { HT , TH , HH } . 6 random sample uncertain sample certain space probability empirical experiment trial outcome space A is defined as any activity or phenomenon that meets the following conditions . 1 . There is one distinct for each trial of the experiment . 2 . The outcome of the experiment is . 3 . The set of all distinct outcomes of the experiment can be specified and is called the , denoted by S . 7 empirical classical probability The of an event ( E ) is obtained by performing a random experiment and computing the ratio of the number of outcomes in which a specified event occurs to the total number of trials . 8 probability Classical small numbers large Empirical relies on the law of , which says that the greater the number of trials , the closer the empirical probability will be to the classical , or actual , probability . 9 probability of law classical small probability large empirical numbers The states that if we continue to roll the die and record the results , the of rolling a particular number should slowly approach its . 10 probability Classical Empirical can be measured as a simple proportion : the number of outcomes that compose the event divided by the number of outcomes in the sample space . 11 table venn tree diagram When an experiment , like tossing a coin three times , is done in stages ( each coin toss could be considered a stage ) , a can be used to organize the outcomes in a systematic manner . The tree begins with the possible outcomes for the first stage and then branches extend from each of these outcomes for the possible outcomes in the second stage , and so on for each stage of the experiment . The sample space is found by following each branch of the tree to identify all the possible outcomes of the experiment . 12 1/2 1 The sum of the probabilities of all outcomes must equal . For example , we know that the sample space of a coin toss includes only two outcomes : heads and tails . The probability of the outcome of a single coin toss being heads is 1 / 2 . Thus , if we sum the probabilities of the two outcomes we have 1 / 2 + 1 / 2 = 1 . 13 to happen never certain If an event has a probability of 1 , then the event is . This occurs when the event includes the entire sample space . 14 definitely happen will never If an event has a probability of 0 , then the event . This occurs when the event is not in the sample space . 15 natural whole rational irrational real The scale used to describe the probability of an event is always a number between 0 and 1 , inclusive . ( Note that the word inclusive means that 0 and 1 are included in the range of numbers . ) 16 Theoretical Empirical means based on , concerned with , or verifiable by observation or experience rather than theory or pure logic : 17 Empirical classical probability is also called experimental probability . 18 empirical Classical probability is also called theoretical probability .
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