The logic and computational details of the one-way independent-samples ANCOVA are described in Chapter 17 of Concepts and Applications.

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This page will perform an analysis of covariance for two independent samples, A and B, where

• A and B represent two quantitative or categorical levels of the independent variable;
  
• DV = the dependent variable of interest; and
  
• CV = the concomitant variable whose effects one wishes to bring under statistical control.

Procedure: For each sample, enter the paired values of CV and DV in the cells of the designated columns, beginning in the top-most cell of each column. Within any particular column, pressing the "tab" key will take you down to the next cell in the column. After all data have been entered, click the "Calculate" button. ~~ If you wish to perform another analysis with a different set of data: click the "Reset" button if the value of n for the largest of your new samples is or smaller; click the "Reload" button if the value of n for the largest of the new samples is greater than .

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Data Entry:
  CV = concomitant variable
  DV = dependent variable_Q

		Levels of Independent Variable
		Sample A			Sample B
count		CV	DV		CV	DV

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Dependent Variable
Sample			Total
A	B
n
Observed Means
Adjusted Means

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Aggregate Correlation within Samples: CV vs DV
r =	r2 =

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ANCOVA SUMMARY

Source	SS	df	MS	F	P
adjusted means
adjusted error
adjusted total

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Test for homogeneity of regressions:

Source	SS	df	MS	F	P
between regressions
remainder
adjusted error

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©Richard Lowry 2001-
All rights reserved.

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