Difference between revisions of "Manuals/calci/NEGBINOMDIST"

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==Examples==
 
==Examples==
  =log 10(5)= 0.698970004
+
#Find the probability that a man flipping a coin gets the fourth head on the ninth flip.
=log(55)= 1.740362689
+
Here total number of events =9, r= 4(since we define Heads as a success) and x=9-4=5(number of failures)
=log(10)= 1
+
p=1/2=0.5(Probability of success for any coin flip)
=log(1)= 0
+
NEGBINOMDIST(5,4,0.5)=0.109375
=log(-10)= NaN
+
#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?
=log(0.25)= -0.602059991
+
Here total number of events=3, r=1,x=3-1=2,and p=0.20
 +
NEGBINOMDIST(2,1,0.20)=0.128
 +
#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==
 
==See Also==

Revision as of 05:05, 26 November 2013

NEGBINOMDIST(nf,ns,ps)


  • Where 'nf' is the number of failures.
  • Where 'ns' is the number of successes on an individual trial
  • And 'ps' is the probability of a success.

Description

This function gives the negative binomial distribution. Negative binomial ditrbution 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:

  1. This experiment consists of a sequence of independent trials.
  2. Each trial represents only two results(Success or failure)
  3. The probability of success is constant from trial to trial
  4. The trials are independent; that is, the outcome on one trial does not affect the outcome on other trials.
  5. 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