In some experiments where we use ANOVA some of the unexplained variability (i.e. the error) is due to some additional variable (called a **covariate**) which is not part of the experiment. If we can somehow remove the effect of this variable, we could reduce the error variance thus enabling us to get a more accurate picture of the true effect of the independent variable. This is the main goal of **Analysis of Covariance** (**ANCOVA**).

Topics:

- Basic concepts
- Regression approach
- Assumptions
- ANOVA approach
- Contrasts
- Tukey’s HSD and Tukey-Kramer
- Effect Size
- Conversion to Stacked Format
- Real Statistics Data Analysis Tools

Great Thank you very much

Sir, is it possible to incorporate Cochran’s Q test and time series analysis to enrich your already rich website. Thank you in advance.

Good idea. I will include Cochran’s Q test in the next release. Time series analysis will have to come a bit later.

Charles