Sunday 22 October 2017

Multiway Data Analysis


Multiway data analysis is a method of analyzing large data sets by representing the data as a multidimensional array. The proper choice of array dimensions and analysis techniques can reveal patterns in the underlying data undetected by other methods.
Multiway data analysts use the term way to refer to a dimension of the data while reserving the word mode for the methods or models used to analyze the data.
In this sense, we can define the various ways of data to analyze:
  • One-way data is a vector, with a single data value for each discrete or continuous value of the single dimension.
  • Two-way data is a matrix, with a single data value for each discrete or continuous value of two separate dimensions; a spreadsheet can be used to visualize such data in the case of discrete dimensions.
  • Three-way data can be viewed as a stack of matrices (or similarly, as a workbook of multiple spreadsheets), adding a third dimension. Such data might represent the temperature at different locations (two-way data) sampled over different times (the third dimension, leading to three-way data)
  • Four-way data, using the same spreadsheet analogy, can be represented as a file folder full of separate workbooks.
  • Five-way data and six-way data can be represented by similarly higher levels of data aggregation.
In general, the several dimensions represented in the data set may be measured at different times, or in different places, using different methodologies, and may contain inconsistencies such as missing data or discrepancies in data representation.
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