Manuals/calci/MULTIPLEREGRESSIONANALYSIS
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
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 |
- =MULTIPLEREGRESSIONANALYSIS(A1:A9,B1:C9,0.05,TRUE)