Multidimensional analysis

In statistics, econometrics, and related fields, multidimensional analysis (MDA) is a data analysis process that groups data into two categories: data dimensions and measurements. For example, a data set consisting of the number of wins for a single football team at each of several years is a single-dimensional (in this case, longitudinal) data set. A data set consisting of the number of wins for several football teams in a single year is also a single-dimensional (in this case, cross-sectional) data set. A data set consisting of the number of wins for several football teams over several years is a two-dimensional data set.

Higher dimensions

In many disciplines, two-dimensional data sets are also called panel data.[1] While, strictly speaking, two- and higher-dimensional data sets are "multi-dimensional", the term "multidimensional" tends to be applied only to data sets with three or more dimensions.[2] For example, some forecast data sets provide forecasts for multiple target periods, conducted by multiple forecasters, and made at multiple horizons. The three dimensions provide more information than can be gleaned from two-dimensional panel data sets.

Software

Computer systems for MDA include Online analytical processing (OLAP) for data in relational databases, and pivot tables, for data in spreadsheets.

See also

References

  1. ↑ Madalla, G. S., 2001. "Introduction to Econometrics", New York: Wiley.
  2. ↑ Davies, A. and K. Lahiri, 1995. "A new framework for testing rationality and measuring aggregate shocks using panel data". Journal of Econometrics, 68(1), 205–227.


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