Adata set (ordataset) is a collection ofdata. In the case oftabular data, a data set corresponds to one or moredatabase tables, where everycolumn of a table represents a particularvariable, and eachrow corresponds to a givenrecord of the data set in question. The data set lists values for each of the variables, such as for example height and weight of an object, for each member of the data set. Data sets can also consist of a collection of documents or files.[2]
In theopen data discipline, a data set is a unit used to measure the amount of information released in a public open data repository. The Europeandata.europa.eu portal aggregates more than a million data sets.[3]
Several characteristics define a data set's structure and properties. These include the number and types of the attributes or variables, and variousstatistical measures applicable to them, such asstandard deviation andkurtosis.[4]
The values may be numbers, such asreal numbers orintegers, for example representing a person's height in centimeters, but may also benominal data (i.e., not consisting ofnumerical values), for example representing a person's ethnicity. More generally, values may be of any of the kinds described as alevel of measurement. For each variable, the values are normally all of the same kind.Missing values may exist, which must be indicated somehow.
Instatistics, data sets usually come from actual observations obtained bysampling astatistical population, and each row corresponds to the observations on one element of that population. Data sets may further be generated byalgorithms for the purpose of testing certain kinds ofsoftware. Some modern statistical analysis software such asSPSS still present their data in the classical data set fashion. If data is missing or suspicious animputation method may be used to complete a data set.[5]
Data sets are widely used across various fields to support data analysis, research, and decision-making. In the sciences, data sets provide the empirical foundation for studies in disciplines such asbiology,physics, andsocial science, enabling discoveries in medicine, environmental science, and social research. Inmachine learning andartificial intelligence, data sets are essential for training, validating, and testing algorithms for tasks such as image recognition, natural language processing, and predictive modeling. Governments and organizations publish open data sets to promote transparency, inform policy-making, and facilitate urban and social planning. The business sector uses data sets for market analysis, customer segmentation, and operational improvements. Additionally, healthcare relies on data sets for clinical research and improving patient outcomes. These varied applications demonstrate the critical role data sets play in enabling evidence-based insights and driving technological progress.
Several classic data sets have been used extensively in thestatistical literature:
