Difference between revisions of "Manuals/calci/FORECAST"

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<div style="font-size:30px">'''FORECAST(n,y,x)'''</div><br/>
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<div style="font-size:30px">'''FORECAST (x,KnownYs,KnownXs) '''</div><br/>
*<math>n</math>  is the data point .
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*<math>x</math>  is the data point .
*<math>y</math>  is the dependent array of data.
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*<math>KnownYs</math>  is the dependent array of data.
*<math>x</math>  is the independent array of data.
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*<math>KnownXs</math>  is the independent array of data.
 
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**FORECAST(), returns a value along a linear trend.
  
 
==Description==
 
==Description==
*This function gives  the predicted value of the dependent variable  for the specific value, x, of the independent variable  by using a least squares  linear regression to predict y values from x values.  
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*This function gives  the predicted value of the dependent variable  for the specific value <math>x</math>, of the independent variable  by using a least squares  linear regression to predict <math>y</math> values from <math>x</math> values.  
*In <math>FORECAST(n,y,x), n</math> is the data point to predict a value. <math>y</math> is the dependent array of data to predict the <math>y</math>-value and <math>x</math> is the independent array of data to predict the <math>y</math>-value.
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*In <math>FORECAST (x,KnownYs,KnownXs)</math>, <math>x</math> is the data point to predict a value.
*The formula for <math>FORECAST</math> is <math> a+bx</math>   
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*<math>KnownYs</math> is the dependent array of data to predict the <math>y</math>-value and <math>KnownXs</math> is the independent array of data to predict the <math>y</math>-value.
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*The formula for <math>FORECAST</math> is <math>a+bx</math>   
 
*where <math>a=\bar{y}-b \bar{x}</math>  and  <math> b=\frac{\sum (x-\bar{x})(y-\bar{y})}{\sum(x-\bar{x})^2}</math>.  
 
*where <math>a=\bar{y}-b \bar{x}</math>  and  <math> b=\frac{\sum (x-\bar{x})(y-\bar{y})}{\sum(x-\bar{x})^2}</math>.  
*Here <math>\bar{x}</math> and <math>\bar{y}</math> are the sample means of x and y.   
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*Here <math>\bar{x}</math> and <math>\bar{y}</math> are the sample means of <math>x</math> and <math>y</math>.   
 
*This function will give the result as error when  
 
*This function will give the result as error when  
   1. Any one of the value is nonnumeric.
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   1. Any one of the value is non-numeric.
   2. The values of x and y are empty or contain a different number of data points.
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   2. The values of <math>KnownXs</math> and <math>KnownYs</math> are empty or contain a different number of data points.
   3. The variance of x is zero.
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   3. The variance of <math>x</math> is zero.
  
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==ZOS==
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 +
*The syntax is to calculate this function in ZOS is <math>FORECAST (x, KnownYs, KnownXs)</math>
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**<math>x</math> is the data points.
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*For e.g.,FORECAST(30,[10,12,16,21,35],[9,14,23,39,76])
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*FORECAST(61,[22..28],[43..49])
  
 
==Examples==
 
==Examples==
#y={5,9,11,18,32,4}
 
x={30,32,15,28,41,10}
 
FORECAST(26,B1:B6,C1:C6)=13.16666667
 
#y={-28,-18,35,12}
 
x={-42,34,-13,25}
 
FORECAST(18,C5:C8,D5:D8)=2.119541779
 
#y={51,14,0,60}
 
x={46,-1,29,18}
 
FORECAST(24,D1:D4,E1:E4)=31.71054889
 
#y={2,5,9,17}
 
x={4,14,28}
 
FORECAST(10,B1:B4,C1:C3)=NAN.
 
  
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{| class="wikitable"
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|+Spreadsheet
 +
|-
 +
! !! A !! B !! C !! D!! E !!F
 +
|-
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! 1
 +
| 5 || 30 || -28 ||-42 ||51 ||46
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|-
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! 2
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| 9 || 32 ||-18 || 34 || 14 || -1
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|-
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! 3
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| 11  || 15  ||35 ||-13|| 0 ||29
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|-
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! 4
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| 18 ||28  ||12  ||25 ||60 ||18
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|-
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! 5
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| 32 || 41 || 2 || 5|| 9 ||17
 +
|-
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! 6
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| 4  || 10 || 4 ||  14 || 28
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|}
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# =FORECAST(26,A1:A6,B1:B6) = 13.16666667
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# =FORECAST(18,C1:C4,D1:D4) = 2.119541779
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# =FORECAST(24,E1:E4,F1:F4) = 31.71054889
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# =FORECAST(10,C5:F5,C6:E6) = NAN.
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==Related Videos==
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{{#ev:youtube|ksCVXXh5_hk|280|center|FORECAST}}
  
 
==See Also==
 
==See Also==
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*[[Manuals/calci/LOGEST| LOGEST ]]
 
*[[Manuals/calci/LOGEST| LOGEST ]]
  
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==References==
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*[https://support.microsoft.com/en-us/kb/828236 FORECAST ]
  
==References==
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 +
 
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*[[Z_API_Functions | List of Main Z Functions]]
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*[[ Z3 |  Z3 home ]]

Latest revision as of 16:07, 10 August 2018

FORECAST (x,KnownYs,KnownXs)


  • is the data point .
  • is the dependent array of data.
  • is the independent array of data.
    • FORECAST(), returns a value along a linear trend.

Description

  • This function gives the predicted value of the dependent variable for the specific value , of the independent variable by using a least squares linear regression to predict values from values.
  • In , is the data point to predict a value.
  • is the dependent array of data to predict the -value and is the independent array of data to predict the -value.
  • The formula for is
  • where and .
  • Here and are the sample means of and .
  • This function will give the result as error when
 1. Any one of the value is non-numeric.
 2. The values of  and  are empty or contain a different number of data points.
 3. The variance of  is zero.

ZOS

  • The syntax is to calculate this function in ZOS is
    • is the data points.
  • For e.g.,FORECAST(30,[10,12,16,21,35],[9,14,23,39,76])
  • FORECAST(61,[22..28],[43..49])

Examples

Spreadsheet
A B C D E F
1 5 30 -28 -42 51 46
2 9 32 -18 34 14 -1
3 11 15 35 -13 0 29
4 18 28 12 25 60 18
5 32 41 2 5 9 17
6 4 10 4 14 28
  1. =FORECAST(26,A1:A6,B1:B6) = 13.16666667
  2. =FORECAST(18,C1:C4,D1:D4) = 2.119541779
  3. =FORECAST(24,E1:E4,F1:F4) = 31.71054889
  4. =FORECAST(10,C5:F5,C6:E6) = NAN.

Related Videos

FORECAST

See Also

References