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  2. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    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]

  3. Thematic analysis - Wikipedia

    en.wikipedia.org/wiki/Thematic_analysis

    Coding reliability [4] [2] approaches have the longest history and are often little different from qualitative content analysis. As the name suggests they prioritise the measurement of coding reliability through the use of structured and fixed code books, the use of multiple coders who work independently to apply the code book to the data, the measurement of inter-rater reliability or inter ...

  4. Exploratory data analysis - Wikipedia

    en.wikipedia.org/wiki/Exploratory_data_analysis

    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."

  5. Quantitative research - Wikipedia

    en.wikipedia.org/wiki/Quantitative_research

    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 ...

  6. Empirical research - Wikipedia

    en.wikipedia.org/wiki/Empirical_research

    Accurate analysis of data using standardized statistical methods in scientific studies is critical to determining the validity of empirical research. Statistical formulas such as regression, uncertainty coefficient, t-test, chi square, and various types of ANOVA (analyses of variance) are fundamental to forming logical, valid conclusions.

  7. Content analysis - Wikipedia

    en.wikipedia.org/wiki/Content_analysis

    The data collection instrument used in content analysis is the codebook or coding scheme. In qualitative content analysis the codebook is constructed and improved during coding, while in quantitative content analysis the codebook needs to be developed and pretested for reliability and validity before coding. [ 4 ]

  8. Cassandre software - Wikipedia

    en.wikipedia.org/wiki/Cassandre_software

    Cassandre is a free open source software for computer assisted qualitative data analysis and interpretation in humanities and social sciences. [1] Although it refers, like other CAQDAS-software, to Grounded Theory Method, it also allows to conduct discourse analysis or quantitative content analysis. [2]

  9. Qualitative comparative analysis - Wikipedia

    en.wikipedia.org/wiki/Qualitative_comparative...

    The small N problem arises when the number of units of analysis (e.g. countries) available is inherently limited. For example: a study where countries are the unit of analysis is limited in that are only a limited number of countries in the world (less than 200), less than necessary for some (probabilistic) statistical techniques.