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  2. Statistical assumption - Wikipedia

    en.wikipedia.org/wiki/Statistical_assumption

    Model-based assumptions. These include the following three types: Distributional assumptions. Where a statistical model involves terms relating to random errors, assumptions may be made about the probability distribution of these errors. [5] In some cases, the distributional assumption relates to the observations themselves. Structural assumptions.

  3. This misconception may originate from a misunderstanding based on the fact that the Earth's mantle convects, and the incorrect assumption that only liquids and gases can convect. In fact, a solid with a large Rayleigh number can also convect, given enough time, which is what occurs in the solid mantle due to the very large thermal gradient ...

  4. Student's t-test - Wikipedia

    en.wikipedia.org/wiki/Student's_t-test

    The assumptions underlying a t-test in the simplest form above are that: X follows a normal distribution with mean μ and variance σ 2 /n. s 2 (n − 1)/σ 2 follows a χ 2 distribution with n − 1 degrees of freedom. This assumption is met when the observations used for estimating s 2 come from a normal distribution (and i.i.d. for each group).

  5. Empirical probability - Wikipedia

    en.wikipedia.org/wiki/Empirical_probability

    In probability theory and statistics, the empirical probability, relative frequency, or experimental probability of an event is the ratio of the number of outcomes in which a specified event occurs to the total number of trials, [1] i.e. by means not of a theoretical sample space but of an actual experiment.

  6. Realization (probability) - Wikipedia

    en.wikipedia.org/wiki/Realization_(probability)

    In probability and statistics, a realization, observation, or observed value, of a random variable is the value that is actually observed (what actually happened). The random variable itself is the process dictating how the observation comes about.

  7. Statistical inference - Wikipedia

    en.wikipedia.org/wiki/Statistical_inference

    Statistical inference makes propositions about a population, using data drawn from the population with some form of sampling.Given a hypothesis about a population, for which we wish to draw inferences, statistical inference consists of (first) selecting a statistical model of the process that generates the data and (second) deducing propositions from the model.

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