The phenomenon that arises when empirical variance in the data exceeds the nominal variance under some assumed model. Most often encountered when modeling data that occurs in the form of proportions or counts, where it is often observed that there is more variation than, for example, an assumed binomial distribution can accommodate.
An observation falling outside the limits 𝐹𝐿 1. 5(𝐹𝑈 𝐹𝐿), 𝐹𝑈 + 1. 5(𝐹𝑈 𝐹𝐿) where F U and F L are the upper and lower quartiles […]
A multidisciplinary field of study that seeks to understand and improve the end results of particular health care practices and interventions.
Two polynomials p i (x) and p j (x) of degree i and j respectively are said to be orthogonal if they are uncorrelated as x varies over some distribution.
A square matrix that is such that multiplying the matrix by its transpose results in an identity matrix.
A term that occurs in several areas of statistics with different meanings in each case. Most commonly encountered in relation to two variables or two linear functions of a set of variables to indicate statistical independence. Literally means ‘at right angles’ but in applied statistics most often used as a descriptive term for the ability to […]
The probability that n random variables X1, X2, . . ., Xn are all positive when the n variates have a joint multivariate normal distribution with all the means zero and all the variances are one. Used, for example, in simultaneous testing.
An aspect of Brownian motion dealing with the velocity of the movement of a particle.
The process of reducing the dimensionality (i.e. the number of variables) of multivariate data by deriving a small number of new variables that contain much of the information in the original data.
A hypothesis that specifies an order for a set of parameters of interest as an alternative to their equality, rather than simply that they are not all equal.
