Data set {{for|IBM mainframe term for a file|Data set (IBM mainframe)}} {{for|The [[ADO.NET]] component|ADO.NET#DataSets}} A '''data set''' (or '''dataset''') is a collection of [[data]], usually presented in tabular form. Each column represents a particular variable. Each row corresponds to a given member of the data set in question. It lists values for each of the variables, such as height and weight of an object or values of random numbers. Each value is known as a [[datum]]. The data set may comprise data for one or more members, corresponding to the number of rows. Historically, the term originated in the [[mainframe computer|mainframe field]], where it had a [[Data set (IBM mainframe)|well-defined meaning]], very close to contemporary ''[[computer file]]''. This topic is not covered here. In the simplest case, there is only one variable, and then the data set consists of a single column of values, often represented as a list. The values may be numbers, such as [[real number]]s or [[integer]]s, for example representing a person's height in centimeters, but may also be [[nominal data]] (i.e., not consisting of [[numerical]] values), for example representing a person's ethnicity. More generally, values may be of any of the kinds described as a [[level of measurement]]. For each variable, the values will normally all be of the same kind. However, there may also be "[[missing values]]", which need to be indicated in some way. In [[statistics]] data sets usually come from actual observations obtained by [[sampling (statistics)|sampling]] a [[statistical population]], and each row corresponds to the observations on one element of that population. Data sets may further be generated by [[algorithms]] for the purpose of testing certain kinds of [[software]]. Some modern statistical analysis software such as [[PSPP]] still present their data in the classical dataset fashion. == Classic data sets == Several classic [[data set]]s have been used extensively in the [[statistical]] literature: * [[Iris flower data set]] - multivariate data set introduced by [[Ronald Fisher]] (1936).{{cite journal|author=Fisher, R.A. |title=The Use of Multiple Measurements in Taxonomic Problems| journal=[[Annals of Eugenics]]| volume=7 |pages=179–188| date=1936| url=http://digital.library.adelaide.edu.au/coll/special//fisher/138.pdf}} * ''[[Categorical data analysis]]'' - Data sets used in the book, ''An Introduction to Categorical Data Analysis'', by Agresti are [http://lib.stat.cmu.edu/datasets/agresti provided on-line by StatLib.] *''[[Robust statistics]]'' - Data sets used in ''Robust Regression and Outlier Detection'' (Rousseeuw and Leroy, 1986). [http://www.uni-koeln.de/themen/Statistik/data/rousseeuw/ Provided on-line at the University of Cologne.] *''[[Time series]]'' - Data used in Chatfield's book, ''The Analysis of Time Series'', are [http://lib.stat.cmu.edu/modules.php?op=modload&name=PostWrap&file=index&page=datasets/ provided on-line by StatLib.] *''Extreme values'' - Data used in the book, ''An Introduction to the Statistical Modeling of Extreme Values'' are [http://homes.stat.unipd.it/coles/public_html/ismev/ismev.dat provided on-line by Stuart Coles], the book's author. *''Bayesian Data Analysis'' - Data used in the book, ''[[Bayesian]] Data Analysis'', are [http://www.stat.columbia.edu/~gelman/book/data/ provided on-line by Andrew Gelman], one of the book's authors. * The [ftp://ftp.ics.uci.edu/pub/machine-learning-databases/liver-disorders Bupa liver data], used in several papers in the machine learning (data mining) literature. ==References== {{reflist}} == External links == * [http://lib.stat.cmu.edu/datasets/ StatLib--Datasets Archive] * [http://lib.stat.cmu.edu/jasadata/ StatLib--JASA Data Archive] * [http://gcmd.nasa.gov GCMD] - The Global Change Master Directory contains more than 20,000 descriptions of Earth science data sets and services covering all aspects of Earth and environmental sciences. [[Category:Computer data]] [[Category:Statistical data sets]] [[pl:Zbiór danych]] {{Comp-sci-stub}}