Abstract
The paper uses two case-studies, one in public health surveillance the other in veterinary epidemiology, to argue that the analysis strategy for spatio-temporal point process data should be guided by the scientific context in which the data were generated and, more particularly, by the objectives of the data analysis. This point of view is not specific to the point process setting and, in the author's opinion, should influence the way that statistics is taught at postgraduate level in response to the emergence and rapid growth of data science.
| Original language | English |
|---|---|
| Article number | 100401 |
| Journal | Spatial Statistics |
| Volume | 37 |
| DOIs | |
| Publication status | Published - 1 Jun 2020 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Data science
- Epidemiology
- Point process
- Teaching
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