Difference between revisions of "Manuals/calci/BINOMDIST"

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<div style="font-size:30px">'''BINOMDIST (ns, ts, ps, cu)'''</div><br/>
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<div style="font-size:30px">'''BINOMDIST (numbers, trials, probability, cumulative)'''</div><br/>
 +
 
 +
*<math>numbers</math> is the number of successes in trials.
 +
*<math>trials</math> is the number of independent trials.
 +
*<math>probability</math> is the probability of success on each trial.
 +
*<math>cumulative</math> is a logical value that determines the form of the function.
 +
**BINOMDIST(), returns the individual term binomial distribution probability.
  
*<math>ns</math> is the number of successes in trials.
 
*<math>ts</math> is the number of independent trials.
 
*<math>ps</math> is the probability of success on each trial
 
*<math>cu</math> is a logical value that determines the form of the function.
 
 
==Description==
 
==Description==
This function gives the individual element Binomial Distribution Probability.We can use this function when the following conditions are satisfied:
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 +
*This function gives the individual element Binomial Distribution Probability.  
 +
*We can use this function when the following conditions are satisfied:
 
#A number of tests <math>n</math> should be fixed.
 
#A number of tests <math>n</math> should be fixed.
 
#Each test must be independent.
 
#Each test must be independent.
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#No test has  any impact on any other test.  
 
#No test has  any impact on any other test.  
 
  For example, the number of ways to achieve 2 heads in a set of four tosses is "4 choose 2".
 
  For example, the number of ways to achieve 2 heads in a set of four tosses is "4 choose 2".
*In BINOMDIST function, <math>ns</math> is the number of successes  in trials.
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*In BINOMDIST function, <math>numbers</math> is the number of successes  in trials.
*TS is the number trials to be made, also <math>ns</math> and <math>ts</math> should be integers.
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*<math>trials</math> is the number trials to be made, also <math>numbers</math> and <math>trials</math> should be integers.
*And <math>ps</math> is number of probability of success on each independent trials.  
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*<math>probability</math> is the number of probability of success on each independent trials.  
*Finally <math>cu</math> is the logical value like TRUE or FALSE. If it is TRUE  it will give the cumulative value or FALSE it will give the exact probability.
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*<math>cumulative</math> is the logical value like TRUE or FALSE. If it is TRUE  it will give the cumulative value or FALSE it will give the exact probability.
 
This function gives result as "Error" when  
 
This function gives result as "Error" when  
#<math>ns</math> and <math>ts</math> are not an Integer.  
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#<math>numbers</math> and <math>trials</math> are not an Integer.  
#<math>ns,ts,ps</math> are not a numeric.
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#<math>numbers,trials,probability</math> are not a numeric.
#<math>ns < 0</math> or <math>ns > ts</math>
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#<math>numbers < 0</math> or <math>numbers > trials</math>
#Also <math>ps < 0</math> or <math>ps >1</math>
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#Also <math>probability < 0</math> or <math>probability >1</math>
Example : =BINOMDIST (4, 12, 0.3, FALSE) is 0.2311
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For Example: =BINOMDIST (4, 12, 0.3, FALSE) is 0.2311
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 +
*The binomial distribution with parameters n and p, we write <math> X \tilde{} B(n, p)</math>.
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*The probability of getting exactly <math> k </math> successes in <math> n </math> trials is given by the Probability Mass Function:
 +
<math> b(k;n,p)=Pr(X = k) = \binom{n}{k}p^{k}(1-p)^{n-k}</math> for k=0,1,2,3...n where  <math>\binom{n}{k}</math> is the COMBIN(n,k) i.e.<math> \binom{n}{k} = \frac{n!}{k!(n-k)}!</math>
  
The binomial distribution with parameters n and p, we write <math> X \tilde{} B(n, p)</math>.
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*The Cumulative Binomial Distribution is:<math>B(x;n,p) = Pr(X \le x) =\sum_{i=0}^x  \binom{n}{i}p^{i}(1-p)^{(n-i)}</math>
The probability of getting exactly <math> k </math> successes in <math> n </math> trials is given by the Probability Mass Function:
 
<math> b(k;n,p)=Pr(X = k) = \binom{n}{k}p^{k}(1-p)^{n-k}</math> for k=0,1,2,3...n where  \binom{n}{k} is the COMBIN(n,k) i.e.<math> \binom{n}{k}=\frac{n!}{k!(n-k)}!</math>
 
  
The Cumulative Binomial Distribution is:<math>B(x;n,p) = Pr(X \le x) =\sum_{n=0}^x  \binom{n}{i}p^{i}(1-p)^{(n-i)}</math>
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==ZOS==
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 +
*The syntax is to calculate <math>BINOMDIST(numbers,trials,probability,cumulative)</math>
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*<math>numbers</math> is the number of successes in trials.
 +
*<math>trials</math> is the number of independent trials.
 +
*<math>probability</math> is the probability of success on each trial.
 +
*<math>cumulative</math> is indicating the form of the function.
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*For e.g.BINOMDIST(9,12,0.2,false)
 +
{{#ev:youtube|v=3PWKQiLK41M|280|center|Binomial Distribution}}
  
 
==Example==
 
==Example==
 +
 
#Toss a coin for 12 times. What is the probability of getting exactly 7 heads.
 
#Toss a coin for 12 times. What is the probability of getting exactly 7 heads.
 
#*Here ns=7,ts=12,and ps=1/2=0.5
 
#*Here ns=7,ts=12,and ps=1/2=0.5
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|12
 
|12
 
|0.5(1/2)
 
|0.5(1/2)
|False
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|FALSE
 
|0.193359375
 
|0.193359375
 
|- class="even"
 
|- class="even"
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|15
 
|15
 
|0.007
 
|0.007
|False
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|FALSE
|0.0428446
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|0.00469597319803066
 
|- class="odd"
 
|- class="odd"
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|Question3
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|2
 +
|10
 +
|0.2
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|TRUE
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|0.6777995264000007
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|- class="even"
  
 
|}
 
|}
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 +
==Related Videos==
 +
 +
{{#ev:youtube|WWv0RUxDfbs|280|center|Binomial Distribution}}
  
 
==See Also==
 
==See Also==
 +
 
*[[Manuals/calci/COMBIN | COMBIN]]
 
*[[Manuals/calci/COMBIN | COMBIN]]
 
*[[Manuals/calci/FACT | FACT]]
 
*[[Manuals/calci/FACT | FACT]]
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==References==
 
==References==
 
[http://en.wikipedia.org/wiki/Binomial_distribution  Binomial Distribution]
 
[http://en.wikipedia.org/wiki/Binomial_distribution  Binomial Distribution]
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*[[Z_API_Functions | List of Main Z Functions]]
 +
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*[[ Z3 |  Z3 home ]]

Latest revision as of 03:30, 25 August 2020

BINOMDIST (numbers, trials, probability, cumulative)


  • is the number of successes in trials.
  •  is the number of independent trials.
  •  is the probability of success on each trial.
  • is a logical value that determines the form of the function.
    • BINOMDIST(), returns the individual term binomial distribution probability.

Description

  • This function gives the individual element Binomial Distribution Probability.
  • We can use this function when the following conditions are satisfied:
  1. A number of tests should be fixed.
  2. Each test must be independent.
  3. Each test represents only two results(Success/Failure)
  4. No test has any impact on any other test.
For example, the number of ways to achieve 2 heads in a set of four tosses is "4 choose 2".
  • In BINOMDIST function, is the number of successes in trials.
  • is the number trials to be made, also and should be integers.
  • is the number of probability of success on each independent trials.
  • is the logical value like TRUE or FALSE. If it is TRUE it will give the cumulative value or FALSE it will give the exact probability.

This function gives result as "Error" when

  1. and are not an Integer.
  2. are not a numeric.
  3. or
  4. Also or
For Example: =BINOMDIST (4, 12, 0.3, FALSE) is 0.2311
  • The binomial distribution with parameters n and p, we write .
  • The probability of getting exactly successes in trials is given by the Probability Mass Function:

for k=0,1,2,3...n where is the COMBIN(n,k) i.e.

  • The Cumulative Binomial Distribution is:

ZOS

  • The syntax is to calculate
  • is the number of successes in trials.
  • is the number of independent trials.
  • is the probability of success on each trial.
  • is indicating the form of the function.
  • For e.g.BINOMDIST(9,12,0.2,false)
Binomial Distribution

Example

  1. Toss a coin for 12 times. What is the probability of getting exactly 7 heads.
    • Here ns=7,ts=12,and ps=1/2=0.5
  1. The LMB Company manufactures tires. They claim that only .007 of LMB tires are defective. What is the probability of finding 2 defective tires in a random sample of 50 LMB tires?
    • Here ns=2,ts=50 and ps=0.007
Questions ns ts ps cu Result
Question 1 7 12 0.5(1/2) FALSE 0.193359375
Question2 2 15 0.007 FALSE 0.00469597319803066
Question3 2 10 0.2 TRUE 0.6777995264000007

Related Videos

Binomial Distribution

See Also

References

Binomial Distribution