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  2. Research design - Wikipedia

    en.wikipedia.org/wiki/Research_design

    A research design typically outlines the theories and models underlying a project; the research question(s) of a project; a strategy for gathering data and information; and a strategy for producing answers from the data. [1] A strong research design yields valid answers to research questions while weak designs yield unreliable, imprecise or ...

  3. Multivariate statistics - Wikipedia

    en.wikipedia.org/wiki/Multivariate_statistics

    Canonical correlation analysis finds linear relationships among two sets of variables; it is the generalised (i.e. canonical) version of bivariate [3] correlation. Redundancy analysis (RDA) is similar to canonical correlation analysis but allows the user to derive a specified number of synthetic variables from one set of (independent) variables ...

  4. Bivariate analysis - Wikipedia

    en.wikipedia.org/wiki/Bivariate_analysis

    Examples are Spearman’s correlation coefficient, Kendall’s tau, Biserial correlation, and Chi-square analysis. Pearson correlation coefficient. Three important notes should be highlighted with regard to correlation: The presence of outliers can severely bias the correlation coefficient.

  5. Design of experiments - Wikipedia

    en.wikipedia.org/wiki/Design_of_experiments

    Design of experiments with full factorial design (left), response surface with second-degree polynomial (right) The design of experiments , also known as experiment design or experimental design , is the design of any task that aims to describe and explain the variation of information under conditions that are hypothesized to reflect the variation.

  6. Exploratory factor analysis - Wikipedia

    en.wikipedia.org/wiki/Exploratory_factor_analysis

    EFA is a technique within factor analysis whose overarching goal is to identify the underlying relationships between measured variables. [1] It is commonly used by researchers when developing a scale (a scale is a collection of questions used to measure a particular research topic) and serves to identify a set of latent constructs underlying a ...

  7. Validity (statistics) - Wikipedia

    en.wikipedia.org/wiki/Validity_(statistics)

    The purpose of experimental designs is to test causality, so that you can infer A causes B or B causes A. But sometimes, ethical and/or methological restrictions prevent you from conducting an experiment (e.g. how does isolation influence a child's cognitive functioning?). Then you can still do research, but it is not causal, it is correlational.

  8. Psychological research - Wikipedia

    en.wikipedia.org/wiki/Psychological_research

    Observational research, (a type of non-experimental, correlational research), involves the researcher observing the ongoing behavior of their subjects. [11] There are multiple methods of observational research such as participant observations, non-participant observations and naturalistic observations. [11]

  9. Reverse correlation technique - Wikipedia

    en.wikipedia.org/wiki/Reverse_correlation_technique

    The reverse correlation technique is a data driven study method used primarily in psychological and neurophysiological research. [1] This method earned its name from its origins in neurophysiology, where cross-correlations between white noise stimuli and sparsely occurring neuronal spikes could be computed quicker when only computing it for segments preceding the spikes.