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It is the quantitative paradigm that prevails in science today, but this is not a purely positive phenomenon, since what seems to be the exact expression of research results is only in fact a guise of absolute objectivity. Effect is given to the laws of nature in space whose structure is not fully known, but certainly heterogeneous, and hence different from the assumptions contained in most mathematical formulae. Indeed, most procedures contain an implicit assumption regarding the homogeneity of space, while the real-life problems relating to the impact of spatial heterogeneity can be seen especially where all kinds of spatial interpolations are applied. Due to heterogeneity of space, seasonality and polygeneticism, natural phenomena are usually characterized by multimodal (multi-peak) distributions of observed variables. Estimation of the mean states from such distributions expressed in terms of the arithmetic mean are inappropriate and in opposition to the basic property of the landscape that is regional differentiation (given that states accepted as representative may in fact be those occurring only rarely or actually precluded in nature). The aim of the work detailed here has therefore been to point out the dangers of undue trust being put in quantitative methods. The essence of progress in science is an increased scope of understanding of phenomena, not the level of detail at which they are described. Without an awareness of the properties of a structure under examination, statistical expressions do not lead to understanding of the principles by which that structure functions. Natural phenomena most often have a log-normal distribution and are polygenetic. A further key problem noted in the initial stages of research therefore relates to proper sampling. Attention is also drawn here to the variability of conditions and states represented by environmental samples, which makes it necessary to use weighted means (especially important where the cycling of matter is being investigated). The article exemplifies problems related to the use of quantitative methods in physical geography, especially in the context of the use of the commonest statistical measures. Apart from the criticism regarding the incautious use of statistical tools, an indication is also given of certain possibilities for statistical measures to be reinterpreted following division of data into subgroups representing specific fragments of space or categories of phenomena. Genetic explanations in a collection of chaotic data are provided for in this way.
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Operational Program Digital Poland, 2014-2020, Measure 2.3: Digital accessibility and usefulness of public sector information; funds from the European Regional Development Fund and national co-financing from the state budget.