Difference between revisions of "Manuals/calci/BERNOULLI"

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*This function will give the result as error when  
 
*This function will give the result as error when  
 
       1. Any one of the argument is nonnumeric.
 
       1. Any one of the argument is nonnumeric.
       2. The value of p<0 or p>1.  
+
       2. The value of p<0 or p>1.
 +
 
 +
==ZOS==
 +
*The syntax is to calculate this function in ZOS is <math>BERNOULLIDISTRIBUTED(a,b)</math>.
 +
**<math>a</math> represents the number of variables.
 +
**<math>b</math>  is the probability value.
 +
*For e.g.,BERNOULLIDISTRIBUTED(5,0.4)
 +
*BERNOULLIDISTRIBUTED(3..7,0.7)
  
 
==Examples==
 
==Examples==

Revision as of 11:04, 4 June 2015

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.

ZOS

  • The syntax is to calculate this function in ZOS is .
    • represents the number of variables.
    • is the probability value.
  • For e.g.,BERNOULLIDISTRIBUTED(5,0.4)
  • BERNOULLIDISTRIBUTED(3..7,0.7)

Examples

  1. =BERNOULLIDISTRIBUTED(5,0.5)=1 1 0 0 1, 0 0 0 0 0
  2. =BERNOULLIDISTRIBUTED(3,0.2)= 0 0 0

Related Videos

Bernoulli Distribution

See Also

References