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  2. Design effect - Wikipedia

    en.wikipedia.org/wiki/Design_effect

    In survey research, the design effect is a number that shows how well ... that computes standard errors for many ... sample size by the design effect. [1]: ...

  3. Sample size determination - Wikipedia

    en.wikipedia.org/wiki/Sample_size_determination

    As the sample size n grows sufficiently large, the distribution of ^ will be closely approximated by a normal distribution. [1] Using this and the Wald method for the binomial distribution, yields a confidence interval, with Z representing the standard Z-score for the desired confidence level (e.g., 1.96 for a 95% confidence interval), in the form:

  4. Questionnaire construction - Wikipedia

    en.wikipedia.org/wiki/Questionnaire_construction

    using questionnaire construction guidelines to inform drafts, such as the Tailored Design Method, [1] or those produced by National Statistical Organisations. Empirical tests also provide insight into the quality of the questionnaire. This can be done by: conducting cognitive interviewing. By asking a sample of potential-respondents about their ...

  5. Research question - Wikipedia

    en.wikipedia.org/wiki/Research_question

    A research question is "a question that a research project sets out to answer". [1] Choosing a research question is an essential element of both quantitative and qualitative research . Investigation will require data collection and analysis, and the methodology for this will vary widely.

  6. Preregistration (science) - Wikipedia

    en.wikipedia.org/wiki/Preregistration_(science)

    In the standard preregistration format, researchers prepare a research protocol document prior to conducting their research. Ideally, this document indicates the research hypotheses, sampling procedure, sample size, research design, testing conditions, stimuli, measures, data coding and aggregation method, criteria for data exclusions, and statistical analyses, including potential variations ...

  7. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]

  8. Design-based research - Wikipedia

    en.wikipedia.org/wiki/Design-Based_Research

    Methodologically, the learning sciences differs from other fields in educational research. It focuses on the study of learners, their localities, and their communities. The design-based research methodology is often used by learning scientists in their inquiries because this methodological framework considers the subject of study to be a complex system involving emergent properties that arise ...

  9. Design science (methodology) - Wikipedia

    en.wikipedia.org/wiki/Design_science_(methodology)

    Design science research (DSR) is a research paradigm focusing on the development and validation of prescriptive knowledge in information science. Herbert Simon distinguished the natural sciences, concerned with explaining how things are, from design sciences which are concerned with how things ought to be, [1] that is, with devising artifacts to attain goals.