Difference Between Ancova and Anova
ANCOVA and ANOVA are statistical techniques used in statistical analysis. Many people get confused with them while making use of it in data analysis. Actually, they are used in researches. One should be careful while using them. Both the techniques are used for equating samples on variables. They can be used for the same purpose with slight difference in methodology.
ANCOVA (Analysis of Covariance) is a method of analysis of two or more variables with at least one continuous and one categorical variable. ANCOVA includes ANOVA. It is called regression in case of ocntinuous. It is a method to test the effect of certain factors on outcome variable when variance is removed. ANCOVA is a linear regression model of analysis.
ANOVA stands for Analysis of Variance. ANOVA is used to check if the data from groups have a common mean or not. This method of analysis prefers to a t-test of two samples as it gives more accurate estimate. When t-tests is used 2 or 3 times there is a probability of error. There is ANOVA is more efficient.
Difference between ANCOVA and ANOVA
ANCOVA and ANOVA are available for the analysis. ANCOVA uses covariance whereas ANOVA does not depend on it. ANOVA has BG variation whereas ANCOVA divides BG variation into TX and COV. Both ANOVA and ANCOVA use WG variation. No doubt, both are good methods of statistical analysis. ANCOVA is supposed to be more powerful and unbiased among the two.