Analysis of Covariance (ANCOVA)

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).

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References

Howell, D. C. (2010) Statistical methods for psychology (7th ed.). Wadsworth, Cengage Learning.
https://labs.la.utexas.edu/gilden/files/2016/05/Statistics-Text.pdf

Schmuller, J. (2009) Statistical analysis with Excel for dummies. Wiley
https://www.wiley.com/en-us/Statistical+Analysis+with+Excel+For+Dummies%2C+3rd+Edition-p-9781118464311

10 thoughts on “Analysis of Covariance (ANCOVA)”

  1. I am comparing between microorganism in different temperature 20& 25 C and I have two factors weights and producing young which analyses will work Charles please. Thank you in advance

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  2. Charles,
    How to perform maximum covariance analysis (MCA) between two time series using real-stat to obtain squared covariance factor (SCF) etc. ? Thank you.

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  3. Which statistical procedure will be applied in this research work ? title is “COMPARATIVE EFFECT OF THREE TYPES AEROBIC TRAINING ON SELECTED PHYSIOLOGICAL AND ANTHROPOMETRIC VARIABLES OF TRIBAL BOYS”
    please inform it. thanks.

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

    Reply

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