Difference between revisions of "Manuals/calci/STEYX"

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<div style="font-size:30px">'''STEYX(y,x)'''</div><br/>
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<div style="font-size:30px">'''STEYX (KnownYs,KnownXs) '''</div><br/>
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*<math>y</math> is set of dependent values.  
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*<math>KnownYs</math> is set of dependent values.  
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*<math>x </math> is the set of independent  values.
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*<math>KnownXs </math> is the set of independent  values.
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**STEYX(),returns the standard error of the predicted y-value for each x in the regression.
  
 
==Description==
 
==Description==
 
*This function gives the standard error of the regression, which also is known as the standard error of the estimate.  
 
*This function gives the standard error of the regression, which also is known as the standard error of the estimate.  
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*It is calculates the  standard error for the straight line of best fit through a supplied set of <math> x </math> and <math> y </math> values.  
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*It is calculates the  standard error for the straight line of best fit through a supplied set of <math> KnownXs</math> and <math> KnownYs</math> values.  
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*The standard error for this line provides a measure of the error in the prediction of <math> y </math> for an individual <math> x </math>.  
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*The standard error for this line provides a measure of the error in the prediction of <math> KnownYs </math> for an individual <math> KnownXs </math>.  
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*The equation for the standard error of the predicted <math> y </math> is: SQRT(1/(n-2)[summation (y-y(bar)^2-[summation (x-x(bar)(y-y(bar)]^2/summation(x-x(bar))^2] ,where x(bar) and y(bar) are the sample mean <math> x </math> and <math> y </math>.
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*The equation for the standard error of the predicted <math> y </math> is:  
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*In <math> STEYX(y,x), y </math> is the array of the numeric dependent values and <math> x </math> is the array of the independent values.   
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<math>\sqrt{\frac{1}{(n-2)}\left [ \sum(y-\bar{y})^2-\frac{[\sum(x-\bar{x})(y-\bar{y})]^2}{\sum(x-\bar{x})^2} \right ]}</math>
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where <math>\bar{x}</math> and <math>\bar{y}</math> are the sample mean <math> x </math> and <math> y </math>.
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*In <math>STEYX (KnownYs,KnownXs)</math>, <math>KnownYs </math> is the array of the numeric dependent values and <math> KnownXs </math> is the array of the independent values.   
 
*The arguments can be be either numbers or names, array,constants or references that contain numbers.  
 
*The arguments can be 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.
 
*Suppose the array contains text,logical values or empty cells, like that values are not considered.
 
*This function will return the result as error when
 
*This function will return the result as error when
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   1. Any one of the argument is nonnumeric.  
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   1. Any one of the argument is non-numeric.  
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   2. x and y are empty or that have less than three data points.
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   2. KnownYs and KnownXs are empty or that have less than three data points.
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   3. x and y have a different number of data points.
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   3. KnownYs and KnownXs  have a different number of data points.
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 +
==Examples==
 +
1.
 +
{| class="wikitable"
 +
|+Spreadsheet
 +
|-
 +
! !! A !! B !! C !! D!! E !!F
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|-
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! 1
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| 6 || 8 || 10 ||13 || 15 ||5
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|-
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! 2
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| 1 || 4 || 8 || 11 || 20 ||3
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|}
  
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=STEYX(A1:F1,A2:F2) = 1.4525201161135368
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2.
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{| class="wikitable"
 +
|+Spreadsheet
 +
|-
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! !! A !! B !! C !! D!! E
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|-
 +
! 1
 +
| 2 || 9 || 1 ||8 || 17
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|-
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! 2
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| 10 || 4 || 11 || 2 || 6
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|}
  
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==Examples==
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  =STEYX(A1:E1,A2:E2)) = 5.944184833375669
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1.y={6,8,10,13,15,5}
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3.
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  x={1,4,9,11,20,3}
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{| class="wikitable"
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STEYX(G1:G6,H1:H6)=1.4350701130
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|+Spreadsheet
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2.y={2,9,1,8,17}
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|-
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x={10,4,11,2,6}
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! !! A !! B !! C !! D!! E
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STEYX(A1:A5,B1:B5)=5.944184833375
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|-
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3.y={1,2,4,5,8}
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! 1
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x={10,4,7,5}
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| 1 || 2 || 4 ||5 || 8  
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STEYX(A1:A5,B1:B4)=NAN
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|-
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! 2
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| 10 || 4 || 7 || 5 ||
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|}
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=STEYX(A1:A5,B1:B4) = NAN
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 +
==Related Videos==
 +
 
 +
{{#ev:youtube|npmg9yvkz3g|280|center|Standard Error Of Estimate}}
  
 
==See Also==
 
==See Also==
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*[[Manuals/calci/LINEST  | LINEST ]]
 
*[[Manuals/calci/LINEST  | LINEST ]]
 
*[[Manuals/calci/PEARSON  | PEARSON ]]
 
*[[Manuals/calci/PEARSON  | PEARSON ]]
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 +
==References==
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*[http://www.ncssm.edu/courses/math/Talks/PDFS/Standard%20Errors%20for%20Regression%20Equations.pdf Standard Error]
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 +
  
  
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==References==
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*[[Z_API_Functions | List of Main Z Functions]]
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*[[ Z3 |  Z3 home ]]

Latest revision as of 14:58, 18 June 2018

STEYX (KnownYs,KnownXs)


  • is set of dependent values.
  • is the set of independent values.
    • STEYX(),returns the standard error of the predicted y-value for each x in the regression.

Description

  • This function gives the standard error of the regression, which also is known as the standard error of the estimate.
  • It is calculates the standard error for the straight line of best fit through a supplied set of and values.
  • The standard error for this line provides a measure of the error in the prediction of for an individual .
  • The equation for the standard error of the predicted is:

where and are the sample mean and .

  • In , is the array of the numeric dependent values and is the array of the independent values.
  • The arguments can be 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.
  • This function will return the result as error when
  1. Any one of the argument is non-numeric. 
  2. KnownYs and KnownXs are empty or that have less than three data points.
  3. KnownYs and KnownXs  have a different number of data points.

Examples

1.

Spreadsheet
A B C D E F
1 6 8 10 13 15 5
2 1 4 8 11 20 3 
=STEYX(A1:F1,A2:F2) = 1.4525201161135368

2.

Spreadsheet
A B C D E
1 2 9 1 8 17
2 10 4 11 2 6 
=STEYX(A1:E1,A2:E2)) = 5.944184833375669

3.

Spreadsheet
A B C D E
1 1 2 4 5 8
2 10 4 7 5 
=STEYX(A1:A5,B1:B4) = NAN

Related Videos

Standard Error Of Estimate

See Also

References



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