Difference between revisions of "Manuals/calci/FORECAST"

Revision as of 06:03, 14 January 2014

FORECAST(n,y,x)

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 $FORECAST(n,y,x),n$ is the data point to predict a value. $y$ is the dependent array of data to predict the $y$ -value and $x$ is the independent array of data to predict the $y$ -value.
The formula for $FORECAST$ is $a+bx$ , where <math>a=\bar{y}-b \bar{x} and b=summation(x-x(bar))(y-y(bar)/summation(x-x(bar))^2. Here x(bar) and y(bar) 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

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

?UNIQee1806e3b9c8b1d6-nowiki-00000002-QINU?

@@ Line 1: / Line 1: @@
-<div id="6SpaceContent" class="zcontent" align="left">
+<div style="font-size:30px">'''FORECAST(n,y,x)'''</div><br/>
+*<math>n</math>  is the data point .
+*<math>y</math>  is the dependent array of data.
+*<math>x</math>  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 <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} and b=summation(x-x(bar))(y-y(bar)/summation(x-x(bar))^2. Here x(bar) and y(bar) 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.
+. The values of x and y are empty or contain a different number of data points.
+. The variance of x is zero.
+ where n, y and x .
 '''FORECAST'''('''x1''',''' ky1’s, kx1’s''')
@@ Line 94: / Line 106: @@
 <div id="5SpaceContent" class="zcontent" align="left">
-<font size="3"><nowiki>=FORECAST (25, C1R1:C1R6, C2R1:C2R6) is 4.7302.</nowiki></font>
+<font size="3">UNIQee1806e3b9c8b1d6-nowiki-00000002-QINU</font>
 </div>
 ----