Statistics Theory L6 = Design Strategies For The Real World Flashcards
How do we define the appropriate spatial or temporal scale? (3)
- Identify an appropriate scale in time/space.
- Consider breadth/length & resolution.
- Design our study to capture the variability across the appropriate scale (1 scale? >1 scale?).
Egs of a Temporal scale? (5)
- Dynamics in insect abundance over time.
- Seasonal?
- Interannual?
- Abundance alone?
- Periodicity or trend?
Egs of Spatial scale? (6)
- Patchy use of landscape by a herbivore.
- Which processes/behaviour?
- Forage selection?
- Movement?
- Home range?
- Migration?
NB about Spatial scale?
Affects space (& time) over which we measure stuff.
Design considerations for time? (2)
- Long-term studies.
- Alternatives to long-term studies.
Long-term studies attributes? (3)
- Important for slow processes, rare events, subtle effects & complex phenomena.
- Important for long-lived organisms (long generation time).
- Systems with slow dynamics (eg, climate change).
Eg of slow processes?
Tectonic shifts.
Eg of rare events?
Volcanic eruptions.
Eg of subtle effects?
Need long time to detect the smallest changes.
Eg of complex phenomena?
Nature.
Alternatives to long-term studies? (4)
- Space for time substitution.
- Retrospective studies.
- Fast dynamics for slow.
- Modeling or simulation.
Design considerations for space?
Spatial replication.
Spatial replication attributes? (3)
- Avoid spatial autocorrelation.
- Avoid pseudo-replication.
- Consider spatially-representative samples.
Spatial autocorrelation?
= the degree to which a spatial variable is correlated with itself across a geographic space.
Spatial autocorrelation attributes? (2)
- Measures how similar or dissimilar nearby locations are in terms of a specific attribute.
- Helps identify patterns in spatial data, such as clustering & dispersion.
Why avoid spatial autocorrelation?
It’s because 2 replicates (eg, plots) that are closer together in a landscape are more similar than 2 distant replicates as they are more likely to be affected by the same processes (climate, soil, disturbance, etc).
Pseudo-replication?
= treating 2 replicate plots from the same site as independent samples.
Why avoid pseudo-replication?
It’s because it leads to inflated degrees of freedom, misleading statistical results & an increased inability to apply the results to the target population.
How to avoid pseudo-replication?
Treat replicates as subsamples within sampling units defined by site.
Why consider Spatially-representative samples?
If we want to make inferences about a particular study area, our samples must cover the whole geographic area.
Thing to note about spatial replication?
Lower correlation = plots are independent.
Error definitions? (3)
= means mistake OR variability OR randomness.
Types of sampling biases? (5)
- Sampling error.
- Non-sampling error.
- Observer bias.
- Measurement bias.
- Selection bias.
- Minimising bias.
Sampling error?
= occurs as the consequence of selecting a subset (i.e., sampling units) from a population for study.