Manuals/calci/MULTIPLEREGRESSIONANALYSIS

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MULTIPLEREGRESSIONANALYSIS(yRange,xRange,ConfidenceLevel,LogicalValue)


  • is the array of y-values.
  • is the array of x-values.
  • is the value betwen 0 and 1.
  • 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:.
  • 2.Multiple regression:.
  • 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:.
  • Multiple Regression:.
  • 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

Spreadsheet
A B C
1 AGE CHOLESTROL LEVEL SUGAR LEVEL
2 58 189 136
3 69 235 149
4 43 198 165
5 39 137 140
6 63 178 162
7 52 160 152
8 47 198 142
9 31 183 129


Related Videos

Multiple Linear Regression

See Also

References