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Index Z-factor

The Z-factor is a measure of statistical effect size. [1]

12 relations: Arithmetic mean, Assay, Effect size, Expected value, High-throughput screening, Normal distribution, Robust statistics, Scientific control, Standard deviation, Standard score, Statistics, Strictly standardized mean difference.

Arithmetic mean

In mathematics and statistics, the arithmetic mean (stress on third syllable of "arithmetic"), or simply the mean or average when the context is clear, is the sum of a collection of numbers divided by the number of numbers in the collection.

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An assay is an investigative (analytic) procedure in laboratory medicine, pharmacology, environmental biology and molecular biology for qualitatively assessing or quantitatively measuring the presence, amount, or functional activity of a target entity (the analyte).

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Effect size

In statistics, an effect size is a quantitative measure of the magnitude of a phenomenon.

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Expected value

In probability theory, the expected value of a random variable, intuitively, is the long-run average value of repetitions of the experiment it represents.

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High-throughput screening

High-throughput screening (HTS) is a method for scientific experimentation especially used in drug discovery and relevant to the fields of biology and chemistry.

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Normal distribution

In probability theory, the normal (or Gaussian or Gauss or Laplace–Gauss) distribution is a very common continuous probability distribution.

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Robust statistics

Robust statistics are statistics with good performance for data drawn from a wide range of probability distributions, especially for distributions that are not normal.

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Scientific control

A scientific control is an experiment or observation designed to minimize the effects of variables other than the independent variable.

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Standard deviation

In statistics, the standard deviation (SD, also represented by the Greek letter sigma σ or the Latin letter s) is a measure that is used to quantify the amount of variation or dispersion of a set of data values.

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Standard score

In statistics, the standard score is the signed number of standard deviations by which the value of an observation or data point differs from the mean value of what is being observed or measured.

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Statistics is a branch of mathematics dealing with the collection, analysis, interpretation, presentation, and organization of data.

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Strictly standardized mean difference

In statistics, the strictly standardized mean difference (SSMD) is a measure of effect size.

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[1] https://en.wikipedia.org/wiki/Z-factor

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