Methods for data standardization

The appropriate standardization method depends on your data set and the conventions of your particular field of study. Examples of papers that discuss standardization include Gower (1985), Johnson and Wichern (1992), Everitt (1993), and van Tongeren (1995). In addition, Milligan and Cooper (1988) present an in-depth examination of standardization of variables when using Euclidean Distance as the dissimilarity metric.

Remember, if you choose to use the Steinhaus Coefficient of Similarity (recommended for count data, such as the number of trees of different species at sampled locations), this measure is self-normalizing and data should not be standardized.

Standardization techniques in BoundarySeer include:

Please note: when you standardize your data and save the data over the original data set, BoundarySeer will not update the maps, charts and tables referencing the data set in your project. Thus, if you query a map, it will show the pre-standardized information, which may be misleading. To view an updated map, chart, or table, delete the old one and create a new one using the standardized data set.

See also: