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  2. Statistical hypothesis test - Wikipedia

    en.wikipedia.org/wiki/Statistical_hypothesis_test

    Null hypothesis (H 0) Positive data: Data that enable the investigator to reject a null hypothesis. Alternative hypothesis (H 1) Suppose the data can be realized from an N(0,1) distribution. For example, with a chosen significance level α = 0.05, from the Z-table, a one-tailed critical value of approximately 1.645 can be obtained.

  3. Kendall's W - Wikipedia

    en.wikipedia.org/wiki/Kendall's_W

    Kendall's W (also known as Kendall's coefficient of concordance) is a non-parametric statistic for rank correlation.It is a normalization of the statistic of the Friedman test, and can be used for assessing agreement among raters and in particular inter-rater reliability.

  4. Scientometrics - Wikipedia

    en.wikipedia.org/wiki/Scientometrics

    Scientometrics is a subfield of informetrics that studies quantitative aspects of scholarly literature.Major research issues include the measurement of the impact of research papers and academic journals, the understanding of scientific citations, and the use of such measurements in policy and management contexts. [1]

  5. Power (statistics) - Wikipedia

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

    Power analysis can either be done before (a priori or prospective power analysis) or after (post hoc or retrospective power analysis) data are collected. A priori power analysis is conducted prior to the research study, and is typically used in estimating sufficient sample sizes to achieve adequate power.

  6. Thesis statement - Wikipedia

    en.wikipedia.org/wiki/Thesis_statement

    The "thesis statement" comes from the concept of a thesis (θέσῐς, thésis) as it was articulated by Aristotle in Topica. Aristotle's definition of a thesis is "a conception which is contrary to accepted opinion." He also notes that this contrary view must come from an informed position; not every contrary view is a thesis. [3]

  7. Cohen's h - Wikipedia

    en.wikipedia.org/wiki/Cohen's_h

    Describe the differences in proportions using the rule of thumb criteria set out by Cohen. [1] Namely, h = 0.2 is a "small" difference, h = 0.5 is a "medium" difference, and h = 0.8 is a "large" difference. [2] [3] Only discuss differences that have h greater than some threshold value, such as 0.2. [4]

  8. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. [1] Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science ...

  9. Yates analysis - Wikipedia

    en.wikipedia.org/wiki/Yates_Analysis

    A Yates analysis generates the following output. A factor identifier (from Yates' order). The specific identifier will vary depending on the program used to generate the Yates analysis. Dataplot, for example, uses the following for a 3-factor model. 1 = factor 1 2 = factor 2 3 = factor 3 12 = interaction of factor 1 and factor 2