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Unformatted text preview: 1 Random variables and probability distributions 2 Random variables are a key concept for statistical inference We know that in order to use results from a sample to infer about a larger population, we must avoid bias and chose a sample at random. If our sample is random, then the sample mean, the sample proportion, and other statistics that we calculate from the sample are called: random variables . The behavior of such variables is an essential step on the way to performing statistical inference. 3 Random variables A random variable X associates a numerical value with each elementary outcome of an experiment Example Let X be the number of boys born in a family of 2 children. List the possible values of X X =1 means that there is one boy in the family 2 children in the family X number of boys BB 2 BG 1 GB 1 GG 4 Probability distribution of discrete variables In order to understand the pattern of behavior of a random variable, we need to know its possible values and how likely they are to occur. The probability distribution of a discrete random variable X is a list of the distinct numerical values of X , along with their associated probabilities. X x 1 x 2 x 3 x k Probability p 1 p 2 p 3 p k 0p i 1 i=1,,k 5 Example If X represents the number of boys in a family of 2 children, find the probability distribution of X. The probability of BB is: p(first is a boy and second is a boy) = p(first is a boy) p(second is a boy)=0.50.5=0.25 P(BG)= P(GB)= P(GG)= Family with 2 children X number of boys Probability BB 2 BG 1 GB 1 GG Since the 2 events are independent 0.25 0.25 0.25 Family with 2 children X number of boys Probability BB 2 0.25 BG 1 0.25 GB 1 0.25 GG 0.25 6 Example  continued Now we can specify the probability of each value of X Family with 2 children X number of boys Probability BB 2 0.25 BG 1 0.25 GB 1 0.25 GG 0.25 Value of X Probability 0.25 1 0.25+0.25=0.5 2 0.25 7 Notations for random variables We denote the random variable by uppercase letters (e.g., X,V,Z ) We denote the values that the random variable gets by lowercase letters (e.g., x i , v i , z i ). The probability that a random variable X get a certain value x is denoted by: p(X=x ) , or, in short , p(x ) . Value of X P(x i ) 0.25 1 0.5 2 0.25 P(X=0)=0.25 P(X=1)=0.5 P(X=2)=0.25 Remember that the sum of the probabilities must equal 1!!! 8 Example A probability distribution is given in the accompanying table with the additional information that the even values of X are equally likely. Determine the missing entries of the table. Value of X P(x) 1 0.2 2 3 0.2 4 5 0.3 6 Answer: The sum of the probabilities in the table: 0.2+0.2+0.3=0.7 The remaining 0.3 probability is equally divided between the values 2,4,and 6 0.1 0.1 0.1 9 Example Here is the probability distribution p(x) for grade X of a randomly chosen student from a certain class....
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This note was uploaded on 11/03/2009 for the course IST IST taught by Professor N/a during the Spring '09 term at Anadolu University.
 Spring '09
 N/A

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