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Analysis of Lognormal Data

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Advances in Soil Science

Part of the book series: Advances in Soil Science ((SOIL,volume 20))

Abstract

The field of statistics exists for the purpose of improving the quality of decisions made from data, and further, to improve the quality of data obtained through experimentation. The field of statistics can be divided roughly into two areas: estimation and comparison. In estimation, the goal is to construct an estimate for a certain attribute (e.g., the rate of microbial respiration for a particular soil) along with some measure of the uncertainty of that estimate. Classic examples include the mean and standard error of the mean and a confidence interval. Testing differences between soils with respect to the rate of denitrification is an example of comparison. The need to make comparisons between batches of numbers (implying populations of attributes) provided much of the impetus for the development of hypothesis-testing methodology currently used by practitioners of statistics. While differing in mechanics, both of these branches of statistics serve to incorporate the impact of uncertainty on decisions made regarding a measured variable. The purpose of this chapter is to delineate methods for estimation and making comparisons between soil processes and properties that exhibit a particular frequency distribution, namely, the two-parameter lognormal distribution. This chapter is not a general review of classical statistical methods and data analytic approaches.

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Authors
  1. T. B. Parkin
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  2. J. A. Robinson
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Editor information

Editors and Affiliations

  1. USDA Conservation & Production Research Laboratory, 79012, Bushland, TX, USA

    B. A. Stewart

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© 1992 Springer-Verlag New York, Inc.

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Parkin, T.B., Robinson, J.A. (1992). Analysis of Lognormal Data. In: Stewart, B.A. (eds) Advances in Soil Science. Advances in Soil Science, vol 20. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-2930-8_4

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  • DOI: https://doi.org/10.1007/978-1-4612-2930-8_4

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4612-7724-8

  • Online ISBN: 978-1-4612-2930-8

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