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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]
The theory of statistics provides a basis for the whole range of techniques, in both study design and data analysis, that are used within applications of statistics. [1] [2] The theory covers approaches to statistical-decision problems and to statistical inference, and the actions and deductions that satisfy the basic principles stated for these different approaches.
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."
Like most research methods, the process of thematic analysis of data can occur both inductively or deductively. [1] In an inductive approach, the themes identified are strongly linked to the data. [4] This means that the process of coding occurs without trying to fit the data into pre-existing theory or framework.
Quantitative research using statistical methods starts with the collection of data, based on the hypothesis or theory. Usually a big sample of data is collected – this would require verification, validation and recording before the analysis can take place. Software packages such as SPSS and R are typically used for this purpose. Causal ...
Data science is "a concept to unify statistics, data analysis, informatics, and their related methods" to "understand and analyze actual phenomena" with data. [5] It uses techniques and theories drawn from many fields within the context of mathematics , statistics, computer science , information science , and domain knowledge . [ 6 ]
The case study method exemplifies qualitative researchers' preference for depth, detail, and context. [11] [12] Data triangulation is also a strategy used in qualitative research. [13] Autoethnography, the study of self, is a qualitative research method in which the researcher uses his or her personal experience to understand an issue.
Once the data are collected, grounded theory analysis involves the following basic steps: Coding text and theorizing: In grounded theory research, the search for a theory starts with the first line of the first interview that one codes. Small chunks of the text are coded line-by-line. Useful concepts are identified where key phrases are marked.