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 software for MDA include Online analytical processing (OLAP) for data in relational databases, pivot tables for data in spreadsheets, and Array DBMSs for general multi-dimensional data (such as raster data) in science, engineering, and business.

gollark: See, I like capitalism but dislike much of how the government works.
gollark: And because of that complexity you need to throw money at lawyers to deal with legal things and may have to settle for a bad outcome *even if you're innocent*.
gollark: The current legal system is in my opinion one of the worst aspects of our society, as the law is so large and complicated that one person literally cannot understand it all and they can be imprisoned due to not knowing.
gollark: You don't need to actually *do* anything. The communist revolution is just inevitable...
gollark: After the communist revolution we'll just make people delete eevil capitalist data.

See also

References
  1. Maddala, G.S. (2001). Introduction to Econometrics (3rd ed.). Wiley. ISBN 0471497282.
  2. Davies, A.; Lahiri, K. (1995). "A new framework for testing rationality and measuring aggregate shocks using panel data". Journal of Econometrics. 68 (1): 205–227. doi:10.1016/0304-4076(94)01649-K.


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