Difference between revisions of "Manuals/calci/HYPGEOMDIST"

From ZCubes Wiki
Jump to navigation Jump to search
Line 18: Line 18:
 
  3.Each individual can be  success (S) or a failure (F),
 
  3.Each individual can be  success (S) or a failure (F),
 
and there are M successes in the population.
 
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:  
+
  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>
 
<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.
 
  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.

Revision as of 05:44, 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.

See Also

References

Correlation