Difference between revisions of "Manuals/calci/BERNOULLI"
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<div style="font-size:30px">'''BERNOULLIDISTRIBUTED(k,p)'''</div><br/> | <div style="font-size:30px">'''BERNOULLIDISTRIBUTED(k,p)'''</div><br/> | ||
*<math>k</math> represents the number of variables. | *<math>k</math> represents the number of variables. | ||
− | *<math>p</math> | + | *<math>p</math> is the probability value. |
==Description== | ==Description== | ||
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*<math>BERNOULLIDISTRIBUTED(k,p)</math> ,<math>k</math> represents the number of variables. | *<math>BERNOULLIDISTRIBUTED(k,p)</math> ,<math>k</math> represents the number of variables. | ||
*<math>p</math> is the probability value. The <math>p</math> vaule is ranges from 0 to 1. | *<math>p</math> is the probability value. The <math>p</math> vaule is ranges from 0 to 1. | ||
− | *The Bernoulli distribution is defined by:<math>f(x)=p^x(1-p)^{1-x}</math> | + | *The Bernoulli distribution is defined by:<math>f(x)=p^x(1-p)^{1-x}</math> for x=0,1, where <math>p</math> is the probability that a particular event will occur. |
*The probability mass function is :<math>f(k,p) = \begin{cases}p &if& k=1\\ | *The probability mass function is :<math>f(k,p) = \begin{cases}p &if& k=1\\ | ||
1-p &if &k=0. | 1-p &if &k=0. |
Revision as of 22:50, 13 February 2014
BERNOULLIDISTRIBUTED(k,p)
- represents the number of variables.
- is the probability value.
Description
- This function gives the value of the Bernoulli distribution.
- It is a discrete probability distribution.
- Bernoulli distribution is the theoretical distribution of the number of successes in a finite set of independent trials with a constant probability of success.
- The Bernoulli distribution is simply BINOM(1,P).
- This distribution best describes all situations where a trial is made resulting in either success or failure, such as when tossing a coin, or when modeling the success or failure.
- , represents the number of variables.
- is the probability value. The vaule is ranges from 0 to 1.
- The Bernoulli distribution is defined by: for x=0,1, where is the probability that a particular event will occur.
- The probability mass function is :
- This function will give the result as error when
1. Any one of the argument is nonnumeric. 2. The value of p<0 or p>1.
Examples
- =BERNOULLIDISTRIBUTED(5,0.5)=1 1 0 0 1, 0 0 0 0 0
- =BERNOULLIDISTRIBUTED(3,0.2)= 0 0 0