Difference between revisions of "Manuals/calci/STDEVP"
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<div style="font-size:30px">'''STDEVP(n1,n2,n3…)'''</div><br/> | <div style="font-size:30px">'''STDEVP(n1,n2,n3…)'''</div><br/> | ||
*<math>n1,n2,n3... </math> are numbers. | *<math>n1,n2,n3... </math> are numbers. | ||
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==Description== | ==Description== | ||
| − | *This function gives the standard deviation based on a entire population | + | *This function gives the standard deviation based on a entire population as the the given data . |
| − | *Standard | + | *Standard Deviation is a quantity expressing by how much the members of a group differ from the mean value for the group. |
*It is the used as a measure of the dispersion or variation in a distribution. | *It is the used as a measure of the dispersion or variation in a distribution. | ||
*It is calculated as the square root of variance. | *It is calculated as the square root of variance. | ||
| − | *In <math>STDEVP(n1,n2,n3...), n1,n2,n3... | + | *In <math>STDEVP(n1,n2,n3...)</math>, <math>n1,n2,n3...</math> are numbers to find the Standard Deviation. |
| − | *Here | + | *Here <math> n1 </math> is required. <math> n2,n3,...</math> are optional. |
*Instead of numbers we can use the single array or a reference of a array. | *Instead of numbers we can use the single array or a reference of a array. | ||
*<math> STDEVP </math> is defined by the formula: | *<math> STDEVP </math> is defined by the formula: | ||
| − | <math>S.D= \sqrt \frac {\sum(x-\bar{x})^2}{(n-1)} </math> where <math> \bar{x} </math> is the sample mean of x and n is the total numbers in the given data. | + | <math>S.D= \sqrt \frac {\sum(x-\bar{x})^2}{(n-1)} </math> |
| + | where <math> \bar{x} </math> is the sample mean of x and n is the total numbers in the given data. | ||
*It is calculated using <math> "n" </math> method. | *It is calculated using <math> "n" </math> method. | ||
| − | *This function is considering our given data | + | *This function is considering our given data as the entire population. |
| − | *Suppose it should consider the data as the sample of the population, we can use the | + | *Suppose it should consider the data as the sample of the population, we can use the [[Manuals/calci/STDEV | STDEV ]] function. |
*For huge sample sizes the functions <math> STDEV </math> and <math> STDEVP </math> are approximately equal values. | *For huge sample sizes the functions <math> STDEV </math> and <math> STDEVP </math> are approximately equal values. | ||
*The arguments can be either numbers or names, array,constants or references that contain numbers. | *The arguments can be either numbers or names, array,constants or references that contain numbers. | ||
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*Suppose the function have to consider the logical values and text representations of numbers in a reference , we can use the [[Manuals/calci/STDEVPA | STDEVPA ]] function. | *Suppose the function have to consider the logical values and text representations of numbers in a reference , we can use the [[Manuals/calci/STDEVPA | STDEVPA ]] function. | ||
*This function will return the result as error when | *This function will return the result as error when | ||
| − | 1. Any one of the argument is | + | 1. Any one of the argument is non-numeric. |
2. The arguments containing the error values or text that cannot be translated in to numbers. | 2. The arguments containing the error values or text that cannot be translated in to numbers. | ||
| − | |||
==Examples== | ==Examples== | ||
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|} | |} | ||
| − | #STDEVP(A1:E1) = 149.0597195757 | + | #=STDEVP(A1:E1) = 149.0597195757 |
| − | #STDEVP(A2:G2) = 76.31463871127 | + | #=STDEVP(A2:G2) = 76.31463871127 |
| − | #STDEVP(A3:E3) = 44.58250778015 | + | #=STDEVP(A3:E3) = 44.58250778015 |
| − | #STDEVP(0,2,8,10,11.7,23.8,32.1,43.7) = 14.389530699435 | + | #=STDEVP(0,2,8,10,11.7,23.8,32.1,43.7) = 14.389530699435 |
==See Also== | ==See Also== | ||
Revision as of 05:43, 30 January 2014
STDEVP(n1,n2,n3…)
- are numbers.
are numbers.Description
- This function gives the standard deviation based on a entire population as the the given data .
- Standard Deviation is a quantity expressing by how much the members of a group differ from the mean value for the group.
- It is the used as a measure of the dispersion or variation in a distribution.
- It is calculated as the square root of variance.
- In , are numbers to find the Standard Deviation.
- Here is required. are optional.
- Instead of numbers we can use the single array or a reference of a array.
- is defined by the formula:
, 
is required. 
are optional.
is defined by the formula:where is the sample mean of x and n is the total numbers in the given data.
where 
is the sample mean of x and n is the total numbers in the given data.
- It is calculated using Failed to parse (syntax error): {\displaystyle "n" } method.
- This function is considering our given data as the entire population.
- Suppose it should consider the data as the sample of the population, we can use the STDEV function.
- For huge sample sizes the functions and are approximately equal values.
- The arguments can be either numbers or names, array,constants or references that contain numbers.
- Suppose the array contains text,logical values or empty cells, like that values are not considered.
- When we are entering logical values and text representations of numbers as directly, then the arguments are counted.
- Suppose the function have to consider the logical values and text representations of numbers in a reference , we can use the STDEVPA function.
- This function will return the result as error when
and 1. Any one of the argument is non-numeric. 2. The arguments containing the error values or text that cannot be translated in to numbers.
Examples
| A | B | C | D | E | F | G | |
|---|---|---|---|---|---|---|---|
| 1 | 87 | 121 | 427 | 390 | 110 | 54 | 32 |
| 2 | 2 | 2.4 | 3.7 | 14.9 | 28 | 198 | 154.1 |
| 3 | 9 | -4 | -29 | 38 | 101 | 19 | 45 |
- =STDEVP(A1:E1) = 149.0597195757
- =STDEVP(A2:G2) = 76.31463871127
- =STDEVP(A3:E3) = 44.58250778015
- =STDEVP(0,2,8,10,11.7,23.8,32.1,43.7) = 14.389530699435