Difference between revisions of "Manuals/calci/NEGBINOMDIST"

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*It is also called Pascal distribution.  
 
*It is also called Pascal distribution.  
 
This is the statistical experiment with the following conditions:
 
This is the statistical experiment with the following conditions:
#This experiment consists of a sequence of independent trials.
+
This experiment consists of a sequence of independent trials.
#Each trial represents only two results(Success or failure)
+
Each trial represents only two results(Success or failure)
#The probability of success is constant from trial to trial
+
The probability of success is constant from trial to trial
#The trials are independent; that is, the outcome on one trial does not affect the outcome on other trials.
+
The trials are independent; that is, the outcome on one trial does not affect the outcome on other trials.
#The experiment continues until r successes are observed,  where r is a specified positive integer.  
+
The experiment continues until r successes are observed,  where r is a specified positive integer.  
 
*The random variable of  x = the number of failures that precede the rth success;  
 
*The random variable of  x = the number of failures that precede the rth success;  
 
*x is called a negative binomial random variable because, in contrast to the  
 
*x is called a negative binomial random variable because, in contrast to the  

Revision as of 07:41, 26 November 2013

NEGBINOMDIST(nf,ns,ps)


  • is the number of failures.
  • is the number of successes on an individual trial
  • is the probability of a success.

Description

  • This function gives the Negative Binomial Distribution.
  • Negative Binomial Distribution is the discrete probability distribution with the fixed probability of success.
  • It is also called Pascal distribution.

This is the statistical experiment with the following conditions:

This experiment consists of a sequence of independent trials.
Each trial represents only two results(Success or failure)
The probability of success is constant from trial to trial
The trials are independent; that is, the outcome on one trial does not affect the outcome on other trials.
The experiment continues until r successes are observed,  where r is a specified positive integer. 
  • The random variable of x = the number of failures that precede the rth success;
  • x is called a negative binomial random variable because, in contrast to the

binomial random variable, the number of successes is fixed and the number of trials is random.

  • Then probability mass function of the negative binomial distribution is:

nb(x;r,p)=(x+r-1 p^r (1-p)^x r-1)

  • For example:If a fair coin is tossed repeatedly, what is the probability that at least 10 tosses are required.

to obtain heads 8 times

  • This function will give the result as error when:
  1. Any argument is nonnumeric
  2. If ps<0 or ps>1
  3. If nf<0 or ns<1

Examples

  1. Find the probability that a man flipping a coin gets the fourth head on the ninth flip.

Here total number of events =9, r= 4(since we define Heads as a success) and x=9-4=5(number of failures)

p=1/2=0.5(Probability of success for any coin flip)

NEGBINOMDIST(5,4,0.5)=0.109375

  1. A company conducts a geological study that indicates that an exploratory goods well should have a 20% chance of striking goods. What is the probability that the first strike comes on the third well drilled?

Here total number of events=3, r=1,x=3-1=2,and p=0.20 NEGBINOMDIST(2,1,0.20)=0.128

  1. What is the probability that the fourth strike comes on the eighth well drilled?

Here total number of events=8, r=4, x=8-4=4 and p=0.20 NEGBINOMDIST(4,4,0.20)=0.0229376

See Also


References

Logarithm