Abstract
INEAR REGRESSION is probably one of the most powerful and useful tools available to the applied statistician. This method uses one or more variables to explain the values of another. Statistics alone cannot prove a cause and effect relationship, but we can show how changes in one set of measurements are associated with changes of the average values in another.
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References
Elston RC and Grizzle JF (1962). Estimation of time response curves and their confidence bands. Biometrics 18: 148–59. Referenced on page 254.
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Zelterman, D. (2015). Multivariable Linear Regression. In: Applied Multivariate Statistics with R. Statistics for Biology and Health. Springer, Cham. https://doi.org/10.1007/978-3-319-14093-3_9
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DOI: https://doi.org/10.1007/978-3-319-14093-3_9
Publisher Name: Springer, Cham
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