Difference between revisions of "Manuals/calci/FORECAST"

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==Examples==
 
==Examples==
 
#y={5,9,11,18,32,4}
 
#y={5,9,11,18,32,4}
x={30,32,15,28,41,10}
+
x={
 
FORECAST(26,B1:B6,C1:C6)=13.16666667
 
FORECAST(26,B1:B6,C1:C6)=13.16666667
#y={-28,-18,35,12}
+
#y={}
 
x={-42,34,-13,25}
 
x={-42,34,-13,25}
 
FORECAST(18,C5:C8,D5:D8)=2.119541779
 
FORECAST(18,C5:C8,D5:D8)=2.119541779
Line 30: Line 30:
 
x={4,14,28}
 
x={4,14,28}
 
FORECAST(10,B1:B4,C1:C3)=NAN.
 
FORECAST(10,B1:B4,C1:C3)=NAN.
 
+
{| class="wikitable"
 +
|+Spreadsheet
 +
|-
 +
! !! A !! B !! C !! D!! E 
 +
|-
 +
! 1
 +
| 5 || 30 || -28 ||-42 ||46
 +
|-
 +
! 2
 +
| 9 || 32 ||-18 || 34 || -1
 +
|-
 +
! 3
 +
| 11  || 15  ||35 ||-13|| 29
 +
|-
 +
! 4
 +
| 18 ||28  ||12  ||25 ||18
 +
|-
 +
! 5
 +
| 32 || 41 ||  || ||
 +
|-
 +
! 6
 +
| 4  || 10
 +
|}
 +
=FORECAST(25,A1:B2,C1:D2) = 16.41772152
  
 
==See Also==
 
==See Also==

Revision as of 00:17, 15 January 2014

FORECAST(n,y,x)


  • is the data point .
  • is the dependent array of data.
  • is the independent array of data.


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.
  • 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 x and y.
  • This function will give the result as error when
 1. Any one of the value is nonnumeric.
 2. The values of x and y are empty or contain a different number of data points.
 3. The variance of x is zero.


Examples

  1. y={5,9,11,18,32,4}

x={ FORECAST(26,B1:B6,C1:C6)=13.16666667

  1. y={}

x={-42,34,-13,25} FORECAST(18,C5:C8,D5:D8)=2.119541779

  1. y={51,14,0,60}

x={46,-1,29,18} FORECAST(24,D1:D4,E1:E4)=31.71054889

  1. y={2,5,9,17}

x={4,14,28} FORECAST(10,B1:B4,C1:C3)=NAN.

Spreadsheet
A B C D E
1 5 30 -28 -42 46
2 9 32 -18 34 -1
3 11 15 35 -13 29
4 18 28 12 25 18
5 32 41
6 4 10

=FORECAST(25,A1:B2,C1:D2) = 16.41772152

See Also


References