Chapter 3 Recap: Univariate analyses

We have learned a multitude of analyses that allowed us to interpret ecological data while depicting the effects of one or multiple variables in one response variable.

We can recall the:

  1. General Linear Models, from which we used the functions:

  2. lm();

  3. anova();

  4. t.test();

  5. lmer().

  6. Generalized Linear Models, where we learned how to apply using:

  7. glm() and glmer() with several family() link functions.

  8. Generalized Additive Models, with the:

  9. gam() function.

These models allowed us to ask questions such as:

  1. What are the effects of precipitation and temperature on species richness?
  2. How does the abundance of microbes change between hosts?
  3. Do co-occurring fish become more aggressive after being induced to fear?

However, one may be interested in making inferences from ecological data containing more than one outcome or dependent variable.

This interest may be driven by hypothesis testing and modelling, but also be entirely exploratory.