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Manuals/calci/MULTIPLEREGRESSIONANALYSIS (view source)
Revision as of 09:11, 5 May 2014
, 09:11, 5 May 2014no edit summary
<div style="font-size:30px">'''MULTIPLEREGRESSIONANALYSIS(yRange,xRange,ConfidenceLevel,LogicalValue)'''</div><br/>
*<math>yRange</math> is the array of y-values.
*<math>xrange</math> is the array of x-values.
*<math>ConfidenceLevel</math> is the value betwen 0 and 1.
*<math>LogicalValue</math> is either TRUE or FALSE.
==Description==
*This function is calculating the Regression analysis of the given data for the multiple array of x values.
*The general purpose of multiple regression is to learn more about the relationship between several independent or predictor variables and a dependent or criterion variable.
*There are two types of Regressions.
1. Simple Regression.
2. Multiple Regression.
*1.Simple Regression:(x_1,Y_1)(x_2,Y_2).......(x_n,Y_n).
*2.Multiple regression:((x1)_1,(x2)_1,(x3)_1.....(xK)_1,Y_1)
((x1)_2,(x2)_2,(x3)_2....(xK)_2,Y_2).......
((x1)_n,(x2)_n,(x3)_n.....(xK)_n,Y_n).
*The only difference between Simple Regression and Multiple Regression is there where one preditor or many.
*i.e., The difference is depending of the x-value.
*The Y is indicated as the "Dependent variable".
*The Predictor x is indicated as the "Independent Variable" .
*The output of a Regression statistics is of the form :
*Simple Regression Y(cap)=b_0+b_1x.
*Multiple Regression Y(cap)=b_0+b_1(x1)+b_2(x2)+......+b_K(xK).
*This analysis give the result in three table values.
1.Regression statistics table.
2.ANOVA table.
3.Residual output.
1.Regression statistics : It contains multiple R, R Square, Adjusted R Square, Standard Error and observations. R square gives the fittness of the data with the regression line.
*That value is closer to 1 is the better the regression line fits the data.
*Standard Error refers to the estimated standard deviation of the error term.
*It is called the standard error of the regression.
*2.ANOVA table: ANOVA is the analysis of variance. This table splits in to two components which is Residual and Regression.
*Also this table gives the probability, T stat, significance of F and P for the each and every set of the data points.
*3. Residual output: The residuals show you how far away the actual data points are fom the predicted data points.
*This table is displaying the values of Predicted data, Standard Residuals and Percentile value of the Y-value.
==Examples==
==Examples==
{| class="wikitable"
{| class="wikitable"