ผลต่างระหว่างรุ่นของ "Probstat/notes/random variables"

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In many cases, after we perform a random experiment, we are interested in certain quantity from the outcome, not the actual outcome.  In that case, we can define a ''random variable'', which is a function from the sample space to real numbers, to represent the random quantity that we are interested in.
 
In many cases, after we perform a random experiment, we are interested in certain quantity from the outcome, not the actual outcome.  In that case, we can define a ''random variable'', which is a function from the sample space to real numbers, to represent the random quantity that we are interested in.
  
For example, consider the following experiment.  We toss two dice.  Let a random variable ''X'' be the sum of the values of these two dice.
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For example, consider the following experiment.  We toss two dice.  Let a random variable ''X'' be the sum of the values of these two dice. The table below shows the outcomes and probabilities related to ''X''.
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 +
{| class="wikitable"
 +
| ''i''
 +
| Outcomes for which ''X'' = ''i''
 +
| Probability ''P{ X = i }''
 +
|-
 +
|2
 +
| (1,1)
 +
| 1/36
 +
|-
 +
|3
 +
| (1,2), (2,1)
 +
| 2/36
 +
|-
 +
|4
 +
| (1,3), (2,2), (3,1)
 +
| 3/36
 +
|-
 +
|5
 +
| (1,4), (2,3), (3,2), (4,1)
 +
| 4/36
 +
|-
 +
|6
 +
| (1,5), (2,4), (3,3), (4,2), (5,1)
 +
| 5/36
 +
|-
 +
|7
 +
| (1,6), (2,5), (3,4), (4,3), (5,2), (6,1)
 +
| 6/36
 +
|-
 +
|8
 +
| (2,6), (3,5), (4,4), (5,3), (6,2)
 +
| 5/36
 +
|-
 +
|9
 +
| (3,6), (4,5), (5,4), (6,4)
 +
| 4/36
 +
|-
 +
|10
 +
| (4,6), (5,5), (6,4)
 +
| 3/36
 +
|-
 +
|11
 +
| (5,6), (6,5)
 +
| 2/36
 +
|-
 +
|12
 +
| (6,6)
 +
| 1/36
 +
|}
  
 
A random variable ''X'' also induces events related to it.  For example, we can consider the event that ''X=10''.
 
A random variable ''X'' also induces events related to it.  For example, we can consider the event that ''X=10''.

รุ่นแก้ไขเมื่อ 02:33, 18 กันยายน 2557

This is part of probstat.

In many cases, after we perform a random experiment, we are interested in certain quantity from the outcome, not the actual outcome. In that case, we can define a random variable, which is a function from the sample space to real numbers, to represent the random quantity that we are interested in.

For example, consider the following experiment. We toss two dice. Let a random variable X be the sum of the values of these two dice. The table below shows the outcomes and probabilities related to X.

i Outcomes for which X = i Probability P{ X = i }
2 (1,1) 1/36
3 (1,2), (2,1) 2/36
4 (1,3), (2,2), (3,1) 3/36
5 (1,4), (2,3), (3,2), (4,1) 4/36
6 (1,5), (2,4), (3,3), (4,2), (5,1) 5/36
7 (1,6), (2,5), (3,4), (4,3), (5,2), (6,1) 6/36
8 (2,6), (3,5), (4,4), (5,3), (6,2) 5/36
9 (3,6), (4,5), (5,4), (6,4) 4/36
10 (4,6), (5,5), (6,4) 3/36
11 (5,6), (6,5) 2/36
12 (6,6) 1/36

A random variable X also induces events related to it. For example, we can consider the event that X=10.