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The Nursing Minimum Data Set (NMDS) is a classification system which allows for the standardized collection of essential nursing data. The collected data are meant to provide an accurate description of the nursing process used when providing nursing care. The NMDS allow for the analysis and comparison of nursing data across populations ...
Mondrian – data analysis tool using interactive statistical graphics with a link to R; Neurophysiological Biomarker Toolbox – Matlab toolbox for data-mining of neurophysiological biomarkers; OpenBUGS; OpenEpi – A web-based, open-source, operating-independent series of programs for use in epidemiology and statistics based on JavaScript and ...
This data is not pre-processed List of GitHub repositories of the project: Red Hat partner This data is not pre-processed List of GitHub repositories of the project: IBM Repositories This data is not pre-processed List of GitHub repositories for the project: Build Lab Team This data is not pre-processed List of GitHub repositories for the project
Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]
Fityk is a curve fitting and data-analysis program. Primarily used for peak fitting and analyzing peak data. FlexPro is a commercial program for interactive and automated analysis and presentation of mainly measurement data. It supports many binary instrument data formats and has its own vectorized programming language.
This is a list of statistical procedures which can be used for the analysis of categorical data, also known as data on the nominal scale and as categorical variables. General tests [ edit ]
For example, the individual components of a differential white blood cell count must all add up to 100, because each is a percentage of the total. Data that is embedded in narrative text (e.g., interview transcripts) must be manually coded into discrete variables that a statistical or machine-learning package can deal with.
This is the aim of multiple factor analysis which balances the different issues (i.e. the different groups of variables) within a global analysis and provides, beyond the classical results of factorial analysis (mainly graphics of individuals and of categories), several results (indicators and graphics) specific of the group structure.