Before you can fit models to data, you have to understand the data you’re plotting. In this lecture we discuss the concept of Data Exploration.
We will spend most of the time discussing the step-by-step model outlined in Zuur et al (2010).
- Understanding study design
- Finding key points from the Methods section in a paper
- Executing an eight-step data exploration:
- Outliers Y & X
- Homogeneity Y
- Normality Y
- Zero trouble Y
- Collinearity X
- Relationships X and Y
- Independence Y
- Do an exercise where we sketch out a study design
- Execute two versions of a data exploration (simple two-variable. Harder full exploration)
For Tuesday Please read:
For Wednesday Please skim:
Loi B, Guala I, Pires da Silva R, Brundu G, Baroli M, Farina S. (2017) Hard time to be parents? Sea urchin fishery shifts potential reproductive contribution of population onto the shoulders of the young adults. PeerJ 5:e3067 https://doi.org/10.7717/peerj.3067
If we are proceeding quickly, we may also try to sketch the study design of:
Peiffer F, Bejarano S, Palavicini de Witte G, Wild C. (2017) Ongoing removals of invasive lionfish in Honduras and their effect on native Caribbean prey fishes. PeerJ 5:e3818 https://doi.org/10.7717/peerj.3818
For historical interest:
- Hurlbert, S.H. (1984). Pseudoreplication and the design of ecological field experiments. Ecological Monographs, 54(2) 187-211
Don’t worry, most data in ecology are pseudoreplicated to some extent and we will discuss ways to deal with that.
Slides via speakerdeck