Data analysis
You don't need to be Editor-In-Chief to add or edit content to WikiDoc. You can begin to add to or edit text on this WikiDoc page by clicking on the edit button at the top of this page. Next enter or edit the information that you would like to appear here. Once you are done editing, scroll down and click the Save page button at the bottom of the page.
Data analysis is the act of transforming data with the aim of extracting useful information and facilitating conclusions. Depending on the type of data and the question, this might include application of statistical methods, curve fitting, selecting or discarding certain subsets based on specific criteria, or other techniques. In contrast to Data mining, data analysis is usually more narrowly intended as not aiming to the discovery of unforeseen patterns hidden in the data, but to the verification or disproval of an existing model, or to the extraction of parameters necessary to adapt a theoretical model to (experimental) reality.
Applications in various fields
Data analysis assumes different aspects, and possibly different names, in different fields.
Nuclear and particle physics
In nuclear and particle physics the data usually originate from the experimental apparatus via a Data acquisition system. It is then processed, in a step usually called data reduction, to apply calibrations and to extract physically significant information. Data reduction is most often, especially in large particle physics experiments, an automatic, batch-mode operation carried out by software written ad-hoc. The resulting data n-tuples are then scrutinized by the physicists, using specialized software tools like ROOT or PAW, comparing the results of the experiment with theory.
The theoretical models are often difficult to compare directly with the results of the experiments, so they are used instead as input for Monte Carlo simulation software like Geant4 that predict the response of the detector to a given theoretical event, producing simulated events which are then compared to experimental data.
See also: Computational physics.
Social sciences
Qualitative data analysis (QDA) or qualitative research is the analysis of non-numerical data, for example words, photographs, observations, etc..
Information technology
A special case is the data analysis in information technology audits.
Business
See
See also
- Censoring (statistics)
- Data acquisition
- Data governance
- Data mining
- Exploratory data analysis
- Predictive analytics
- Qualitative research
- Scientific computing
- Test method
Further reading
- Michael S. Lewis-Beck, Data Analysis: an Introduction, Sage Publications Inc, 1995, ISBN 0803957726
- Pyzdek, T, "Quality Engineering Handbook", 2003, ISBN 0824746147
- Godfrey, A. B., "Juran's Quality Handbook", 1999, ISBN 007034003
- "Engineering Statistics Handbook", NIST/SEMATEK, [1]
- "Manual on Presentation of Data and Control Chart Analysis", ASTM MNL 7, 1990, ISBN:0-8031-1189-0fr:Analyse des données (statistiques)
Acknowledgement and Attribution Regarding Sources of Content
Some of the initial content on this page may be incorporated in part from copyleft sources in the public domain including wikis such as Wikipedia and AskDrWiki. Drug information for patients came from the The National Library of Medicine. Infectious disease information may have come from the Centers for Disease Control (CDC). Differential Diagnoses are drawn from clinicians as well as an amalgamation of 3 sources: 1.The Disease Database; 2. Kahan, Scott, Smith, Ellen G. In A Page: Signs and Symptoms. Malden, Massachusetts: Blackwell Publishing, 2004:3; 3. Sailer, Christian, Wasner, Susanne. Differential Diagnosis Pocket. Hermosa Beach, CA: Borm Bruckmeir Publishing LLC, 2002:7 .
