Difference between revisions of "Manuals/calci/REGRESSION"

From ZCubes Wiki
Jump to navigation Jump to search
Line 55: Line 55:
  
 
{| class="wikitable"
 
{| class="wikitable"
 +
|+Summary Output
 
|-
 
|-
 
! Regression !! Statistics
 
! Regression !! Statistics
Line 68: Line 69:
  
 
{| class="wikitable"
 
{| class="wikitable"
|+Spreadsheet
+
|+ANOVA
 
|-
 
|-
 
! Source of Variation!! Sum Of Squares !! Degree Of Freedom !! Mean Of Squares !! F!! Significance F
 
! Source of Variation!! Sum Of Squares !! Degree Of Freedom !! Mean Of Squares !! F!! Significance F

Revision as of 00:29, 23 January 2014

REGRESSIONANALYSIS(y,x)


  • is the set of dependent variables .
  • is the set of independent variables.


Description

  • This function is calculating the Regression analysis of the given data.
  • This analysis is very useful for the analyzation of large amounts of data and making predictions.
  • 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.
  • Total sum of squares= Residual (error) sum of squares+ Regression (explained) sum of squares.
  • Also this table gives the probability, T stat, significance of F and P.
  • When the significance of F is < 0.05, then the result for the given data is statistically significant.
  • When the significance of F is > 0.05, then better to stop using this set of independent variables.
  • Then remove a variable with a high P-value and returnun the regression until Significance F drops below 0.05.
  • So the Significance of P value should be <0.05.
  • This table containing the regression coefficient values also.
  • 3.Residual output:
  • The residuals show you how far away the actual data points are fom the predicted data points.


Examples

Spreadsheet
A B
1 Temperature Drying Time(Hrs)
2 54 8
3 63 6
4 75 3
5 82 1
=REGRESSIONANALYSIS(A2:A5,B2:B5)
Summary Output
Regression Statistics
Multiple R -0.9989241524588298
R Square 0.9978494623655915
v14193 0.9967741935483871
v15308 0.7071067811865362
ANOVA
Source of Variation Sum Of Squares Degree Of Freedom Mean Of Squares F Significance F
Regression: 464 1 464 928 0.0010758475411702228
Residual 1 2 0.5
Total 465 3


Unit sales - Ads - population 4000 - 12000 - 300000 5200 - 13150 - 411000 6800 - 14090 - 500000 8000 - 11900 - 650000 10000 - 15000 - 800000 REGRESSIONANALYSIS(B1:B5,C1:D5)=

See Also

References