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Encyclopedia of GIS pp 2086–2100Cite as

Spatial Statistics and Geostatistics: Basic Concepts

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Historical Background

Statisticians have recognized impacts of correlated observations since the inception of their discipline. For example, in the early 1800s, while developing bivariate normal curve theory, Laplace acknowledged that between day variations in barometric pressure readings tend to be much greater than within day readings (Stigler 1986, p. 151). This thinking occurred during the emergence of multivariate statistics, being inspired in part by Lagrange’s contribution of the multivariate normal distribution in the early 1800s (Stigler 1986, ‘p. 118). Ultimately, statisticians developed both multivariate data analysis theory and its extension to correlated sample situations (e.g., the difference of correlated means, Hotelling (1931); the difference of correlated variances, Pitman (1939); the difference of correlated correlation coefficients, Dunn and Clark (1971)). Addressing variable correlation concerns spawned the addressing of observation correlation concerns in the...

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References

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Author information

Authors and Affiliations

  1. Geospatial Information Sciences, School of Economic, Political and Policy Sciences, University of Texas at Dallas, 800 W. Campbell Rd, 75080-3021, Richardson, TX, USA

    Daniel Griffith

Authors
  1. Daniel Griffith
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Correspondence to Daniel Griffith .

Editor information

Editors and Affiliations

  1. University of Minnesota, Minneapolis, MN, USA

    Shashi Shekhar

  2. Management Science and Information Systems Department, Rutgers Business School, Rutgers, The State University of New Jersey, Newark, NJ, USA

    Hui Xiong

  3. Department of Management Sciences, Tippie College of Business, University of Iowa, Iowa City, IA, USA

    Xun Zhou

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Griffith, D. (2017). Spatial Statistics and Geostatistics: Basic Concepts. In: Shekhar, S., Xiong, H., Zhou, X. (eds) Encyclopedia of GIS. Springer, Cham. https://doi.org/10.1007/978-3-319-17885-1_1650

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