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Data science is multifaceted and can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession. [4] Data science is "a concept to unify statistics, data analysis, informatics, and their related methods" to "understand and analyze actual phenomena" with data. [5]
A data product is a computer application that takes data inputs and generates outputs, feeding them back into the environment. [41] It may be based on a model or algorithm. For instance, an application that analyzes data about customer purchase history, and uses the results to recommend other purchases the customer might enjoy. [42] [13]
Chemometrics is the science of relating measurements made on a chemical system or process to the state of the system via application of mathematical or statistical methods. Demography is the statistical study of all populations. It can be a very general science that can be applied to any kind of dynamic population, that is, one that changes ...
Data about applicant's family and various other factors included. 12,960 Text Classification 1997 [480] [481] V. Rajkovic et al. University Dataset Data describing attributed of a large number of universities. None. 285 Text Clustering, classification 1988 [482] S. Sounders et al. Blood Transfusion Service Center Dataset
Computational statistics, or statistical computing, is the study which is the intersection of statistics and computer science, and refers to the statistical methods that are enabled by using computational methods. It is the area of computational science (or scientific computing) specific to the mathematical science of statistics. This area is ...
A time series is the sequence of a variable's value over equally spaced periods, such as years or quarters in business applications. [11] To accomplish this, the data must be smoothed, or the random variance of the data must be removed in order to reveal trends in the data. There are multiple ways to accomplish this.
But the mapping of computer science data types to statistical data types depends on which categorization of the latter is being implemented. Other categorizations have been proposed. For example, Mosteller and Tukey (1977) [22] distinguished grades, ranks, counted fractions, counts, amounts, and balances.
Data processing is the collection and manipulation of digital data to produce meaningful information. [1] Data processing is a form of information processing , which is the modification (processing) of information in any manner detectable by an observer.