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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]
SPSS Statistics is a statistical software suite developed by IBM for data management, advanced analytics, multivariate analysis, business intelligence, and criminal investigation. Long produced by SPSS Inc. , it was acquired by IBM in 2009.
Two main statistical methods are used in data analysis: descriptive statistics, which summarize data from a sample using indexes such as the mean or standard deviation, and inferential statistics, which draw conclusions from data that are subject to random variation (e.g., observational errors, sampling variation). [4]
Statistica is a suite of analytics software originally developed by StatSoft and acquired by Dell in March 2014. The software includes an array of data analysis, data management, data visualization, and data mining procedures; as well as a variety of predictive modeling, clustering, classification, and exploratory techniques. [2]
The software's primary applications are for designed experiments and analyzing statistical data from industrial processes. [7] JMP can be used in conjunction with the R and Python open source programming languages to access features not available in JMP itself. [42] JMP software is partly focused on exploratory data analysis and visualization.
The terms 'computational statistics' and 'statistical computing' are often used interchangeably, although Carlo Lauro (a former president of the International Association for Statistical Computing) proposed making a distinction, defining 'statistical computing' as "the application of computer science to statistics", and 'computational ...
Tukey defined data analysis in 1961 as: "Procedures for analyzing data, techniques for interpreting the results of such procedures, ways of planning the gathering of data to make its analysis easier, more precise or more accurate, and all the machinery and results of (mathematical) statistics which apply to analyzing data."
As statistics and data sets have become more complex, [a] [b] questions have arisen regarding the validity of models and the inferences drawn from them. There is a wide range of conflicting opinions on modelling. Models can be based on scientific theory or ad hoc data analysis, each employing different methods. Advocates exist for each approach ...