Difference between revisions of "Manuals/calci/FORECAST"

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*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.  
 
*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 <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), 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.
*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>. Here <math>\bar{x}</math> and <math>\bar{y}</math> are the sample means of x and y.   
+
*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>.  
 +
*Here <math>\bar{x}</math> and <math>\bar{y}</math> are the sample means of x and y.   
 
*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.
 
   1. Any one of the value is nonnumeric.

Revision as of 05:23, 14 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.
where n, y and x .

FORECAST(x1, ky1’s, kx1’s)

Where X1   is the data point, ky1 is the dependent array or range of data and ky2

is the independent array or range of data.


It Predicts or calculates a future value by using existing values. The predicted value is a y1-value for a given x1-value.


·          FORECAST displays an error, when x is nonnumeric.

·          when the variance of kx1’s equals zero FORECAST displays errror.

·          The equation for FORECAST is a+bx, where:

and:

and where x and y are the sample means AVERAGE(kx1's) and AVERAGE(ky1's).


FORECAST

Syntax

Remarks

Examples

Description

Column1 Column2 Column3 Column4
Row1 4 25 4.730174
Row2 5 23
Row3 8 32
Row4 17 36
Row5 22 40 0
Row6

AVEDEV (N1, N2...) Where N1, N 2 ...   are positive integers.

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