Difference between revisions of "Manuals/calci/FORECAST"
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*<math>y</math> is the dependent array of data. | *<math>y</math> is the dependent array of data. | ||
*<math>x</math> is the independent array of data. | *<math>x</math> is the independent array of data. | ||
| − | |||
==Description== | ==Description== | ||
| − | *This function gives the predicted value of the dependent variable for the specific value | + | *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. | + | *In <math>FORECAST(n,y,x)</math>, <math>n</math> is the data point to predict a value. |
| − | *The formula for <math>FORECAST</math> is <math> a+bx</math> | + | *<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. |
| + | *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. | + | *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 | + | 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. | + | 2. The values of <math>x</math> and <math>y</math> are empty or contain a different number of data points. |
| − | 3. The variance of x is zero. | + | 3. The variance of <math>x</math> is zero. |
| − | |||
==Examples== | ==Examples== | ||
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*[[Manuals/calci/LINEST | LINEST]] | *[[Manuals/calci/LINEST | LINEST]] | ||
*[[Manuals/calci/LOGEST| LOGEST ]] | *[[Manuals/calci/LOGEST| LOGEST ]] | ||
| − | |||
==References== | ==References== | ||
Revision as of 22:57, 23 January 2014
FORECAST(n,y,x)
- is the data point .
- is the dependent array of data.
- is the independent array of data.
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 , 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
, 
is 
and 
.
and 
are the sample means of 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.
Examples
| 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 |
- =FORECAST(26,A1:A6,B1:B6) = 13.16666667
- =FORECAST(18,C1:C4,D1:D4) = 2.119541779
- =FORECAST(24,E1:E4,F1:F4) = 31.71054889
- =FORECAST(10,C5:F5,C6:E6) = NAN.