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Data wrangling typically follows a set of general steps which begin with extracting the data in a raw form from the data source, "munging" the raw data (e.g. sorting) or parsing the data into predefined data structures, and finally depositing the resulting content into a data sink for storage and future use. [1]
Data analysis is a process for obtaining raw data, and subsequently converting it into information useful for decision-making by users. [1] Data is collected and analyzed to answer questions, test hypotheses, or disprove theories.
BIN – binary data, often memory dumps of executable code or data to be re-used by the same software that originated it; DAT – data file, usually binary data proprietary to the program that created it, or an MPEG-1 stream of Video CD; DSK – file representations of various disk storage images; RAW – raw (unprocessed) data
Data envelopment analysis (DEA) is a nonparametric method in operations research and economics for the estimation of production frontiers. [1] DEA has been applied in a large range of fields including international banking, economic sustainability, police department operations, and logistical applications [2] [3] [4] Additionally, DEA has been used to assess the performance of natural language ...
Raw data is a relative term (see data), because even once raw data have been "cleaned" and processed by one team of researchers, another team may consider these processed data to be "raw data" for another stage of research. Raw data can be inputted to a computer program or used in manual procedures such as analyzing statistics from a survey.
Data dredging (also known as data snooping or p-hacking) [1] [a] is the misuse of data analysis to find patterns in data that can be presented as statistically significant, thus dramatically increasing and understating the risk of false positives.
Prior to analysis, raw data (or unprocessed data) is typically cleaned: Outliers are removed, and obvious instrument or data entry errors are corrected. Data can be seen as the smallest units of factual information that can be used as a basis for calculation, reasoning, or discussion.
Multiple factor analysis (MFA) is a factorial method [1] devoted to the study of tables in which a group of individuals is described by a set of variables (quantitative and / or qualitative) structured in groups. It is a multivariate method from the field of ordination used to simplify multidimensional data structures. MFA treats all involved ...