Difference between revisions of "Manuals/calci/HYPGEOMDIST"

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<div style="font-size:30px">'''HYPGEOMDIST(n1,n2,n3,n4)'''</div><br/>
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<div style="font-size:20px">'''HYPGEOMDIST (sample_s,number_sample,population_s,number_population,cumulative)'''</div><br/>
*<math>n1</math> is the sample's success.
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*<math>samples</math> is the sample's success.
*<math>n2</math> is the sample's size.
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*<math>number sample</math> is the sample's size.
*<math>n3</math> is population's success.
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*<math>population s</math> is population's success.
*<math>n4</math> is the population size.
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*<math>number population</math> is the population size.
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**HYPGEOMDIST(),returns the hypergeometric distribution.
  
 
==Description==
 
==Description==
*This function gives the result of Hypergeometric distribution.
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*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 hypergeometric random variable is the number of successes that result from a hypergeometric experiment.  
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*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.
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*The probability distribution of a Hypergeometric random variable is called a Hypergeometric Distribution.
*In  HYPGEOMDIST(n1,n2,n3,n4) where n1 is thenumber of items in the Sample  that are classified as successes.  
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*In  HYPGEOMDIST (sample_s,number_sample,population_s,number_population,cumulative) where samples is the number of items in the Sample  that are classified as successes.  
*n2 is the total number of items in the sample.
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*<math>number sample</math> is the total number of items in the sample.
*n3 is thenumber of items in the population  that are classified as successes and n4 is the total number of items in the sample.  
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*<math>populations</math> is the number of items in the population  that are classified as successes and <math>numberpopulation</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:  
#This distribution is applies to sampling without replacement from a finite population whose elements can be classified into two categories like success or Failure.
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1.This distribution is applies to sampling without replacement from a finite population whose elements can be
#The population or set to be sampled consists of N individuals, objects,or elements  
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classified into two categories like Success or Failure.
#Each individual can be  success (S) or a failure (F),
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2.The population or set to be sampled consists of N individuals, objects,or elements  
and there areM successes in the population.
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3.Each individual can be  success (S) or a failure (F), and there are M successes in the population.
#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:  
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4.A sample of <math>n</math> individuals is selected without replacement in such a way that each subset of  
P(X=x)=h(x;n,M,N)=(M          (N-M
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  size <math>n</math> is equally likely to be chosen.
                                    x)          n-x)        /(N   
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*The Hyper geometric probability distribution is:
                                                                      n)  for x is an integer satisfying  max(0, n-N+M)<=x<=min(n,M). where x is sample's success.
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<math>\frac{\binom{m}{x}  \binom{N-M}{n-x}}{\binom{m}{x}}</math>
*n is the sample's size.
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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.
*M is population's success and N is the population size.  
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*<math>n</math> is the sample's size.
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*<math>M</math> is population's success and <math>N</math> 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  
#Any one of the argument is nonnumeric.
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1.Any one of the argument is non-numeric.
#n1<0 or n1 is greater than the smaller value of n2 or n3.
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2.<math>samples < 0</math> or samples is greater than the smaller value of numbersample or populations.
#n1 is less than the bigger of 0 or(n2-n4+n3)
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3.<math>samples</math> is less than the bigger of 0 or(numbersample-numberpopulation+populations)
#n2<=0 or n2>n4
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4.<math>numbersample \le 0</math> or <math>numbersample>numberpopulation</math>
#n3<=0 or  n3>n4 or n4<=0"
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5.<math>populations \le 0</math> or  <math>populations>numberpopulation</math> or <math>numberpopulation \le 0</math>
 +
 
 +
==ZOS==
 +
*The syntax is to calculate HYPGEOMDIST in ZOS is <math>HYPGEOMDIST (sample s,number sample,population s,number population,cumulative)
 +
</math>
 +
**<math>sample s</math> is the sample's success.
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**<math>number sample</math> is the sample's size.
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**<math>population s</math> is population's success.
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**<math>number population</math> is the population size.
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*For e.g.,HYPGEOMDIST(2..3,6..7,9..10,20)
 +
 
 +
{{#ev:youtube|fui0xWgBO4g|280|center|Hyper-geometric Distribution}}
  
 
==Examples==
 
==Examples==
  
Draw 6 cards from a deck without replacement.
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#Draw 6 cards from a deck without replacement.What is the probability of getting two hearts?
What is the probability of getting two hearts?
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Here M = 13 number of hearts
Here M = 13 number of hearts
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N = 52 total number of cards
N = 52 total number of cards
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so N-M= 52-13= 39 and  
so N-M= 52-13= 39 and  
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x=2,n=6 so n-x=6-2=4
x=2,n=6 so n-x=6-2=4
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=HYPGEOMDIST(2,6,13,52)=0.315129882
HYPGEOMDIST(2,6,13,52)=0.315129882
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#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
2.42 balls are numbered 1 - 42.
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(i)Here M= 6,N=42,x=3and n=6
You select six numbers between 1 and 42. What is the probability that they contain
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HYPGEOMDIST(3,6,6,42)=0.02722185
(i)match 3?
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(ii)Here M= 6,N=42,x=4and n=6
(ii) match 4?
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HYPGEOMDIST(4,6,6,42)=0.001801446
(i)Here M= 6,N=42,x=3and n=6
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HYPGEOMDIST(3,6,6,42)=0.02722185
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==Related Videos==
(ii)Here M= 6,N=42,x=4and n=6
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HYPGEOMDIST(4,6,6,42)=0.001801446
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{{#ev:youtube|NMeVWPdo7e4|280|center|Hyper-Geometric Distribution}}
3.
 
  
 
==See Also==
 
==See Also==
Line 58: Line 70:
  
 
==References==
 
==References==
[http://en.wikipedia.org/wiki/Pearson_product-moment_correlation_coefficient| Correlation]
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[http://en.wikipedia.org/wiki/Hypergeometric_distribution| Hypergeometric Distribution]
 +
 
 +
 
 +
 
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*[[Z_API_Functions | List of Main Z Functions]]
 +
 
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*[[ Z3 |  Z3 home ]]

Latest revision as of 17:19, 7 August 2018

HYPGEOMDIST (sample_s,number_sample,population_s,number_population,cumulative)


  • is the sample's success.
  • is the sample's size.
  • is population's success.
  • is the population size.
    • HYPGEOMDIST(),returns the hypergeometric distribution.

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 (sample_s,number_sample,population_s,number_population,cumulative) where samples 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  individuals is selected without replacement in such a way that each subset of 
  size  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 samples is greater than the smaller value of numbersample or populations.
3. is less than the bigger of 0 or(numbersample-numberpopulation+populations)
4. or 
5. or   or 

ZOS

  • The syntax is to calculate HYPGEOMDIST in ZOS is
    • is the sample's success.
    • is the sample's size.
    • is population's success.
    • is the population size.
  • For e.g.,HYPGEOMDIST(2..3,6..7,9..10,20)
Hyper-geometric Distribution

Examples

  1. 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
  1. 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

Related Videos

Hyper-Geometric Distribution

See Also

References

Hypergeometric Distribution