Difference between revisions of "Manuals/calci/VARA"

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<div style="font-size:30px">'''VARA(n1,n2,n3…)'''</div><br/>
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<div style="font-size:30px">'''VARA()'''</div><br/>
*<math>n1,n2,n3,... </math>  are numbers.
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*Parameters are set of numbers.
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**VARA(),estimates variance based on a sample, including numbers, text, and logical values.
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==Description==
 
==Description==
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*i.e.,variance  is a measure of how far each value in the data set is from the mean.
 
*i.e.,variance  is a measure of how far each value in the data set is from the mean.
 
*It is denoted by <math> \sigma </math>. The square root of variance is called the standard deviation.  
 
*It is denoted by <math> \sigma </math>. The square root of variance is called the standard deviation.  
*In <math>VARA(n1,n2,n3,...)</math>, <math>n1,n2,n3,...</math> are numbers based on a sample of a population. Here <math>n1</math> is required. <math>n2,n3,...</math> are optional.  
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*In <math>VARA()</math>, Parameters are set of numbers based on a sample of a population. Here First Parameter is required. From the second Parameter are optional.  
 
*To find the variance we can use the following formula:  
 
*To find the variance we can use the following formula:  
 
<math>Variance= \frac{\sum (x_i-\bar{x})^2}{n-1}</math>  
 
<math>Variance= \frac{\sum (x_i-\bar{x})^2}{n-1}</math>  
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#VARA(A2:E2)=21.0852299999
 
#VARA(A2:E2)=21.0852299999
 
#VARA(A3:E3)=34.3
 
#VARA(A3:E3)=34.3
#VARA(10,15,20,25,FALSE)=41.666666666
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#VARA(10,15,20,25,FALSE)=92.5
#VARA(10,15,20,25,TRUE)=85.699
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#VARA(10,15,20,25,TRUE)=85.69999999999999
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==Related Videos==
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{{#ev:youtube|2evEY6MTxZQ|280|center|Sample Variance}}
  
 
==See Also==
 
==See Also==
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==References==
 
==References==
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*[http://en.wikipedia.org/wiki/Variance Variance]
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*[[Z_API_Functions | List of Main Z Functions]]
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*[[ Z3 |  Z3 home ]]

Latest revision as of 16:30, 8 August 2018

VARA()


  • Parameters are set of numbers.
    • VARA(),estimates variance based on a sample, including numbers, text, and logical values.


Description

  • This function gives the variance based on a sample.
  • Variance is a measure of dispersion obtained by taking the mean of the squared deviations of the observed values from their mean in a frequency distribution.
  • i.e.,variance is a measure of how far each value in the data set is from the mean.
  • It is denoted by . The square root of variance is called the standard deviation.
  • In , Parameters are set of numbers based on a sample of a population. Here First Parameter is required. From the second Parameter are optional.
  • To find the variance we can use the following formula:

where is the sample mean of and is the sample size.

  • Suppose which is indicating all the values are identical.
  • When is non-zero then it is always positive.
  • This function is considering our given data is the sample of the population.
  • Suppose it should consider the data as the entire population, we can use the VARPA function.
  • The arguments can be be either numbers or names, array,constants or references that contain numbers.
  • Also we can give the text representations of numbers or logical values , like TRUE or FALSE, in a reference.
  • Suppose the arguments containing TRUE which is eveluate as 1, and the arguments containing FALSE which is evaluate as 0.
  • Suppose the array contains the empty cells and text values like that values are not considered.
  • Suppose the function don't want to consider the logical values and text representations of numbers in a reference , we can use the VAR function.
  • This function will return the result as error when
      1. Any one of the argument is nonnumeric. 
      2. The arguments containing the error values or text that cannot be translated in to numbers.

Examples

Spreadsheet
A B C D E F G H I J
1 78 61 53 46 24 19 82 90 45 10
2 10.25 16.74 18.09 20.43 22.22 11.98 24 19 10 75
3 2 5 10 15 true 81 10 27 24 39
  1. VARA(A1:J1)=756.6222222223
  2. VARA(A2:E2)=21.0852299999
  3. VARA(A3:E3)=34.3
  4. VARA(10,15,20,25,FALSE)=92.5
  5. VARA(10,15,20,25,TRUE)=85.69999999999999

Related Videos

Sample Variance

See Also

References