The GeoMed/Epi Project:

Quotes

"...everything is related to everything else, but near things are more related than distant things." Tobler (1970), quoted in Upton and Fingleton, Spatial Data Analysis by Example, p. 186.
'One of the early researchers to make use of maps in this way was Petermann, who constructed maps of cholera mortality for the British Isles in 1852. He described the advantages of using maps to display medical information as follows:
"The object, therefore, in constructing Cholera Maps is to obtain a view of the geographical extent of the ravages of this disease, and to discover the local conditions that might influence its progress and its degree of fatality. For such a purpose, geographical delineation is of the utmost value, and even indispensable; for while the symbols of the masses of statistical data in figures, however clearly they might be arranged in systematic tables, present but a uniform appearance, the same data, embodied in a map, will convey at once, the relative bearing and proportion of the single data together with their position, extent, and distance, and thus, a map will make visible to the eye the development and nature of any phenomenon in regards to its geographical distribution." (1)'
"...a pattern is not necessarily indicative of the process which produced it." Hudson and Fowler (1966, p. 7), quoted in Upton and Fingleton, Spatial Data Analysis by Example, p. 12.
"A concept without a concrete illustration is empty." Stephen Jay Gould, lecture at the U. of M., 1998. For the record, he also defined a fact: "A fact is something so well affirmed that it would be perverse to withhold assent."
"THE REAL PROBLEM is that in most (potential) applications of geostatistics there are no state equations from which one could derive the model parameters or verify the underlying assumptions, hence the variogram, the assumption of second order or intrinsic stationarity (or multi-variate normality) become just that, they are assumptions. As yet all purported inference tests depend on random sampling (random site selection is not random sampling) or strong distributional assumptions such as multi-variate normality. The problem is ILL_POSED, i.e., we do not have enough information to make a unique inference about the values at non-data locations. To do so we must make model assumptions and then the question is how strongly do our results depend on the model assumptions and how strongly on the data?" Don Myers, University of Arizona, from an email of 12/7/98 to the ai-geostats@gis.psu.edu group.
Cliff and Ord, on spatial autocorrelation:
- "If the presence of some quality in a county of a country makes its presence in neighbouring counties more or less likely, we say that the phenomenon exhibits spatial autocrrelation." Cliff and Ord, "Spatial Autocorrelation", p. 2.
- "...the presence of spatial autocorrelation may be attributable either to trends (or gradients) in the data or to interactions....
  "When we develop a model for a spatial process, we must always ask whether the levels of the process at two (neighboring) sites reflect interaction (between the sites) or reaction to some other variable.... When reaction is the major influence, a regression model is appropriate, whereas interactive effects suggest the need for a model with a spatially dependent covariance structure." Cliff and Ord, "Spatial Processes", p. 141.
"...as the issue of computational intensity subsides, and GIS software becomes increasingly user-friendly, more ubiquitously available, and a source for implementing spatial statistical techniques, the danger of malpractice by the non-specialist practitioner grows." Daniel Griffith, in "Practical Handbook of Spatial Statistics", CRC Press, 1996.
About the Poisson process:
- "The Poisson process is a mathematical concept and no real phenomenon can be expected to be exactly in accord with it." Cox and Lewis, quoted in "Spatial Processes: models and applications", by Cliff and Ord.
- "...a Poisson process over a planar surface is the outcome of sampling jointly from two independent uniform distributions." Griffith, D. A. 1992. Teaching Spatial Statistics to Geographers Using MINITAB. Journal of Geography in Higher Education, 16:1. pp. 45-59.
On problem solving:
When the only tool you own is a hammer, every problem begins to resemble a nail. Abraham Maslow
"We may at once admit that any inference from the particular to the general must be attended with some degree of uncertainty, but this is not the same as to admit that such inference cannot be absolutely rigorous, for the nature and degree of the uncertainty may itself be capable of rigorous expression. In the theory of probability, as developed in its application to games of chance, we have the classic example proving this possibility. If the gambler's apparatus are really true or unbiased, the probabilities of the different possible events, or combinations of events, can be inferred by a rigorous deductive argument, although the outcome of any particular game is recognised to be uncertain. The mere fact that inductive inferences are uncertain cannot, therefore, be accepted as precluding perfectly rigorous and unequivocal inference." R. A. Fisher (1935).
"Humility is indeed wise for the spatial analyst!" Bailey and Gatrell (1995)

Website maintained by Andy Long. Comments appreciated.

longa@nku.edu