Difference between revisions of "Manuals/calci/NEGBINOMDIST"
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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; | + | The trials are independent; ie, the outcome on one trial does not affect the outcome on other trials. |
− | The experiment continues | + | The experiment continues until <math>r</math> successes are observed, where <math>r</math> is a specified positive integer. |
− | *The random variable of x = the number of failures that precede the | + | *The random variable of <math>x</math> = the number of failures that precede the <math>r^th</math> success; |
− | *x is called a | + | *<math>x</math> 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. | 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: | *Then probability mass function of the negative binomial distribution is: | ||
nb(x;r,p)=(x+r-1 p^r (1-p)^x r-1) | 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. | + | *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 | to obtain heads 8 times | ||
*This function will give the result as error when: | *This function will give the result as error when: |
Revision as of 06:44, 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; ie, the outcome on one trial does not affect the outcome on other trials. The experiment continues until successes are observed, where is a specified positive integer.
- The random variable of = the number of failures that precede the success;
- 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:
- Any argument is nonnumeric
- If ps<0 or ps>1
- If nf<0 or ns<1
Examples
- 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
- 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
- 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