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  2. Pulse wave velocity - Wikipedia

    en.wikipedia.org/wiki/Pulse_wave_velocity

    The theory of the velocity of the transmission of the pulse through the circulation dates back to 1808 with the work of Thomas Young. [9] The relationship between pulse wave velocity (PWV) and arterial wall stiffness can be derived from Newton's second law of motion (=) applied to a small fluid element, where the force on the element equals the product of density (the mass per unit volume ...

  3. Moens–Korteweg equation - Wikipedia

    en.wikipedia.org/wiki/Moens–Korteweg_equation

    The Moens–Korteweg equation states that PWV is proportional to the square root of the incremental elastic modulus, (E inc), of the vessel wall given constant ratio of wall thickness, h, to vessel radius, r, and blood density, ρ, assuming that the artery wall is isotropic and experiences isovolumetric change with pulse pressure.

  4. Welch–Satterthwaite equation - Wikipedia

    en.wikipedia.org/wiki/Welch–Satterthwaite_equation

    In statistics and uncertainty analysis, the Welch–Satterthwaite equation is used to calculate an approximation to the effective degrees of freedom of a linear combination of independent sample variances, also known as the pooled degrees of freedom, [1] [2] corresponding to the pooled variance.

  5. Prediction interval - Wikipedia

    en.wikipedia.org/wiki/Prediction_interval

    Given a sample from a normal distribution, whose parameters are unknown, it is possible to give prediction intervals in the frequentist sense, i.e., an interval [a, b] based on statistics of the sample such that on repeated experiments, X n+1 falls in the interval the desired percentage of the time; one may call these "predictive confidence intervals".

  6. Compositional data - Wikipedia

    en.wikipedia.org/wiki/Compositional_data

    In probability and statistics, a partition of the sampling space into disjoint events is described by the probabilities assigned to such events. The vector of D probabilities can be considered as a composition of D parts. As they add to one, one probability can be suppressed and the composition is completely determined.

  7. Inverse-variance weighting - Wikipedia

    en.wikipedia.org/wiki/Inverse-variance_weighting

    For normally distributed random variables inverse-variance weighted averages can also be derived as the maximum likelihood estimate for the true value. Furthermore, from a Bayesian perspective the posterior distribution for the true value given normally distributed observations and a flat prior is a normal distribution with the inverse-variance weighted average as a mean and variance ().