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  2. Data collection - Wikipedia

    en.wikipedia.org/wiki/Data_collection

    The goal for all data collection is to capture evidence that allows data analysis to lead to the formulation of credible answers to the questions that have been posed. Regardless of the field of or preference for defining data ( quantitative or qualitative ), accurate data collection is essential to maintain research integrity.

  3. Quantitative research - Wikipedia

    en.wikipedia.org/wiki/Quantitative_research

    Quantitative methods are an integral component of the five angles of analysis fostered by the data percolation methodology, [10] which also includes qualitative methods, reviews of the literature (including scholarly), interviews with experts and computer simulation, and which forms an extension of data triangulation. Quantitative methods have ...

  4. SPSS - Wikipedia

    en.wikipedia.org/wiki/SPSS

    IDA (Interactive Data Analysis) [27] was a software package that originated at what was formerly the National Opinion Research Center , at the University of Chicago. Initially offered on the HP-2000 , [ 28 ] somewhat later, under the ownership of SPSS, it was also available on MUSIC/SP . [ 29 ]

  5. Coding (social sciences) - Wikipedia

    en.wikipedia.org/wiki/Coding_(social_sciences)

    For quantitative analysis, data is coded usually into measured and recorded as nominal or ordinal variables.. Questionnaire data can be pre-coded (process of assigning codes to expected answers on designed questionnaire), field-coded (process of assigning codes as soon as data is available, usually during fieldwork), post-coded (coding of open questions on completed questionnaires) or office ...

  6. Exploratory factor analysis - Wikipedia

    en.wikipedia.org/wiki/Exploratory_factor_analysis

    Exploratory Factor Analysis Model. In multivariate statistics, exploratory factor analysis (EFA) is a statistical method used to uncover the underlying structure of a relatively large set of variables. EFA is a technique within factor analysis whose overarching goal is to identify the underlying relationships between measured variables. [1]

  7. 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]

  8. Q methodology - Wikipedia

    en.wikipedia.org/wiki/Q_methodology

    Q methodology is a research method used in psychology and in social sciences to study people's "subjectivity"—that is, their viewpoint. Q was developed by psychologist William Stephenson . It has been used both in clinical settings for assessing a patient's progress over time (intra-rater comparison), as well as in research settings to ...

  9. Multiple factor analysis - Wikipedia

    en.wikipedia.org/wiki/Multiple_factor_analysis

    The small size and simplicity of the example allow simple validation of the rules of interpretation. But the method will be more valuable when the data set is large and complex. Other methods suitable for this type of data are available. Procrustes analysis is compared to the MFA in. [2]

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