Analysis of Covariance

Often we are dealing with experiments or studies in which more than one treatment is applied simultaneously and we want to know what’s their relative effect on the response variable. In case we are manipulating a continuous variable and a categorical one, the parametric analysis traditionally used to assess their relative importance is the Analysis of Covariance (ANCOVA).

Example: let’s consider the chirps of two cricket species and check if their pulse rate differ across a temperature gradient. This is a study that was actually performed by Walker (1962) on species Oecanthus exclamationis and Oecanthus niveus.

Graph displaying the response of pulse at different temperatures (continuous explanatory variable) in two different species (species identity is the categorical variable).
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Two-way ANOVA

Often we are dealing with experiments or studies with more than one explanatory variable. In such situation, more than one treatment is applied simultaneously and we want to know what’s their relative effect on the response variable. If both explanatory variables are categorical, the analysis traditionally used is a Two-way ANOVA.

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Online resources for statistics and/or R

The internet is a near-endless mine of information. There are all too many good on-line resources about statistics and/or R to cite them all, but here are some that I use often: