Difference between revisions of "Manuals/calci/BERNOULLIDISTRIBUTED"

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  2. The value of p<0 or p>1.
 
  2. The value of p<0 or p>1.
  
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==Examples==
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#BERNOULLIDISTRIBUTED(5,0.5) = 0  0  0  0  1
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#BERNOULLIDISTRIBUTED(9,0.8) = 0 1 1 1 1 1 1 1 1
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#BERNOULLIDISTRIBUTED(4,0.87) = 1  1  1  0
  
\begin{cases}
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==Related Videos==
3x + 5y +  z &= 1 \\
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7x - 2y + 4z &= 2 \\
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{{#ev:youtube|v=O8vB1eInP_8|280|center|Bernoulli Distribution}}
-6x + 3y + 2z &= 3
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\end{cases}
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==See Also==
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*[[Manuals/calci/BERNOULLI | BERNOULLI]]
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*[[Manuals/calci/KURT | KURT]]
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*[[Manuals/calci/MULTINOMIAL | MULTINOMIAL]]
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==References==
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[http://mathworld.wolfram.com/BernoulliDistribution.html  Bernoulli Distribution]
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*[[Z_API_Functions | List of Main Z Functions]]
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*[[ Z3 |  Z3 home ]]

Latest revision as of 16:00, 4 December 2018

BERNOULLIDISTRIBUTED (Numbers,Probability)


  • is the number of variables.
  • is the value range from 0 to 1.

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.
  • In , 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 p 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 non numeric.
2. The value of p<0 or p>1.

Examples

  1. BERNOULLIDISTRIBUTED(5,0.5) = 0 0 0 0 1
  2. BERNOULLIDISTRIBUTED(9,0.8) = 0 1 1 1 1 1 1 1 1
  3. BERNOULLIDISTRIBUTED(4,0.87) = 1 1 1 0

Related Videos

Bernoulli Distribution

See Also

References

Bernoulli Distribution