Analysis of Covariance for 3 Independent Samples

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

This page will perform an analysis of covariance for three independent samples, A, B, and C, where
• A, B, and C represent three 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 .

Data Entry:
CV = concomitant variable
DV = dependent variable
 Levels of Independent Variable Sample A Sample B Sample C count CV DV CV DV CV DV

 Dependent Variable Sample Total A B C n Observed Means Adjusted Means

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

ANCOVA SUMMARY