Difference between revisions of "Manuals/calci/HYPGEOMDIST"
Jump to navigation
Jump to search
Line 6: | Line 6: | ||
==Description== | ==Description== | ||
− | *This function gives the result of Hypergeometric | + | *This function gives the result of Hypergeometric Distribution. |
*This distribution is a discrete probability distribution which is contrast to the binomial distribution. | *This distribution is a discrete probability distribution which is contrast to the binomial distribution. | ||
− | *A | + | *A Hypergeometric random variable is the number of successes that result from a Hypergeometric experiment. |
− | *The probability distribution of a | + | *The probability distribution of a Hypergeometric random variable is called a Hypergeometric Distribution. |
− | *In HYPGEOMDIST(n1,n2,n3,n4) where n1 is | + | *In HYPGEOMDIST(n1,n2,n3,n4) where n1 is the number of items in the Sample that are classified as successes. |
− | *n2 is the total number of items in the sample. | + | *<math>n2</math> is the total number of items in the sample. |
− | *n3 is | + | *<math>n3</math> is the number of items in the population that are classified as successes and <math>n4</math> is the total number of items in the sample. |
*The following conditions are applied to the Hypergeometric distribution: | *The following conditions are applied to the Hypergeometric distribution: | ||
− | + | 1.This distribution is applies to sampling without replacement from a finite population whose elements can be classified into two categories like Success or Failure. | |
− | + | 2.The population or set to be sampled consists of N individuals, objects,or elements | |
− | + | 3.Each individual can be success (S) or a failure (F), | |
− | and there | + | and there are M successes in the population. |
− | + | 4.A sample of n individuals is selected without replacement in such a way that each subset of size n is equally likely to be chosen. The Hyper geometric probability distribution is: | |
− | + | <math>\frac{\binom{m}{x} \binom{N-M}{n-x}}{\binom{m}{x}}</math> | |
− | + | for <math>x</math> is an integer satisfying <math>max(0, n-N+M)<=x<=min(n,M)</math>. where <math>x</math> is sample's success. | |
− | + | *<math>n</math> is the sample's size. | |
− | *n is the sample's size. | + | *<math>M</math> is population's success and <math>N</math> is the population size. |
− | *M is population's success and N is the population size. | ||
*Here we can give any positive real numbers. | *Here we can give any positive real numbers. | ||
*Suppose we are assigning any decimals numbers it will change in to Integers. | *Suppose we are assigning any decimals numbers it will change in to Integers. | ||
*This function will give result as error when | *This function will give result as error when | ||
− | + | 1.Any one of the argument is non-numeric. | |
− | + | 2.<math>n1 < 0</math> or n1 is greater than the smaller value of n2 or n3. | |
− | + | 3.<math>n1</math> is less than the bigger of 0 or(n2-n4+n3) | |
− | + | 4.<math>n2 \le 0</math> or <math>n2>n4</math> | |
− | + | 5.<math>n3 \le 0</math> or <math>n3>n4</math> or <math>n4 \le 0</math> | |
==Examples== | ==Examples== |
Revision as of 05:43, 10 December 2013
HYPGEOMDIST(n1,n2,n3,n4)
- is the sample's success.
- is the sample's size.
- is population's success.
- is the population size.
Description
- This function gives the result of Hypergeometric Distribution.
- This distribution is a discrete probability distribution which is contrast to the binomial distribution.
- A Hypergeometric random variable is the number of successes that result from a Hypergeometric experiment.
- The probability distribution of a Hypergeometric random variable is called a Hypergeometric Distribution.
- In HYPGEOMDIST(n1,n2,n3,n4) where n1 is the number of items in the Sample that are classified as successes.
- is the total number of items in the sample.
- is the number of items in the population that are classified as successes and is the total number of items in the sample.
- The following conditions are applied to the Hypergeometric distribution:
1.This distribution is applies to sampling without replacement from a finite population whose elements can be classified into two categories like Success or Failure. 2.The population or set to be sampled consists of N individuals, objects,or elements 3.Each individual can be success (S) or a failure (F),
and there are M successes in the population.
4.A sample of n individuals is selected without replacement in such a way that each subset of size n is equally likely to be chosen. The Hyper geometric probability distribution is:
for is an integer satisfying . where is sample's success.
- is the sample's size.
- is population's success and is the population size.
- Here we can give any positive real numbers.
- Suppose we are assigning any decimals numbers it will change in to Integers.
- This function will give result as error when
1.Any one of the argument is non-numeric. 2. or n1 is greater than the smaller value of n2 or n3. 3. is less than the bigger of 0 or(n2-n4+n3) 4. or 5. or or
Examples
Draw 6 cards from a deck without replacement. What is the probability of getting two hearts? Here M = 13 number of hearts N = 52 total number of cards so N-M= 52-13= 39 and x=2,n=6 so n-x=6-2=4 HYPGEOMDIST(2,6,13,52)=0.315129882 2.42 balls are numbered 1 - 42. You select six numbers between 1 and 42. What is the probability that they contain (i)match 3? (ii) match 4? (i)Here M= 6,N=42,x=3and n=6 HYPGEOMDIST(3,6,6,42)=0.02722185 (ii)Here M= 6,N=42,x=4and n=6 HYPGEOMDIST(4,6,6,42)=0.001801446 3.