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In statistics and research design, an index is a composite statistic – a measure of changes in a representative group of individual data points, or in other words, a compound measure that aggregates multiple indicators. [1] [2] Indices – also known as indexes and composite indicators – summarize and rank specific observations. [2]
In statistics, an effect size is a value measuring the strength of the relationship between two variables in a population, or a sample-based estimate of that quantity. It can refer to the value of a statistic calculated from a sample of data, the value of one parameter for a hypothetical population, or to the equation that operationalizes how statistics or parameters lead to the effect size ...
Ordinal indicators are sometimes written as superscripts (1 st, 2 nd, 3 rd, 4 th, rather than 1st, 2nd, 3rd, 4th), although many English-language style guides recommend against this use. [4] Romance languages use a similar convention, such as 1 er or 2 e in French, or 4ª and 4º in Galician and Italian, or 4.ª and 4.º in Portuguese and Spanish.
Random variables are usually written in upper case Roman letters, such as or and so on. Random variables, in this context, usually refer to something in words, such as "the height of a subject" for a continuous variable, or "the number of cars in the school car park" for a discrete variable, or "the colour of the next bicycle" for a categorical variable.
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For example, in the above five-point Likert item, the inference is that the 'distance' between category 1 and 2 is the same as between category 3 and 4. In terms of good research practice, an equidistant presentation by the researcher is important; otherwise a bias in the analysis may result.
3. Between two groups, may mean that the first one is a proper subgroup of the second one. > (greater-than sign) 1. Strict inequality between two numbers; means and is read as "greater than". 2. Commonly used for denoting any strict order. 3. Between two groups, may mean that the second one is a proper subgroup of the first one. ≤ 1.
The Fowlkes–Mallows index is an external evaluation method that is used to determine the similarity between two clusterings (clusters obtained after a clustering algorithm), and also a metric to measure confusion matrices. This measure of similarity could be either between two hierarchical clusterings or a clustering and a benchmark ...