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Copyright

Stuart N. Lane;

Published On

2025-02-25

Page Range

pp. 571–576

Language

  • English

Print Length

6 pages

42. Statistical inference

Chapter of: The Field Guide to Mixing Social and Biophysical Methods in Environmental Research(pp. 571–576)
Statistical inference is a widely used method in both social and biophysical science that aims to allow statements about a (larger) population from a sample of that population. It is partly a question of using statistical methods to allow you to make a statement about a population with a certain probability, defined by characteristics of your data, including the size of the sample you have. However, it is also a question of research design, that is how you collect data (size of sample, sampling method) in a way that allows you to do the inference correctly. The results of statistical inference need particular care because inference is effectively a method that allows you to establish how confident you are that the properties of your data are also properties of the population (e.g. is the correlation in your data also found in your population). Statistical inference does not tell you about whether that property (e.g. correlation) is strong or not, which is a question of judgement. Equally, inference should not be blind to questions of causality; the simple existence of a statistically significant relation does not necessarily imply that the relation is causal. It may simply be spurious.

Contributors

Stuart Lane

(author)
Professor of Geomorphology at University of Lausanne
https://orcid.org/0000-0002-6077-6076

Stuart N. Lane is Professor of Geomorphology at the University of Lausanne. He is a geographer and civil engineer by training who has held posts at the Universities of Cambridge, Leeds and Durham in the U.K. and Lausanne in Switzerland. His work has sought to bring a geographical perspective to contemporary environmental concerns such as flooding and pollution. The primary focus of his current work is the environments created by disappearing glaciers in terms of ice, water, sediment and ecosystems and the consequences of these changes for environmental management. An important thread through his most recent research criticizes the current alignment of geography as a discipline with the ever more neo-liberal academy; and then argues for the rediscovery of a more scientific geographical science better able to cope with the crises the world is experiencing today.