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A sample is random if the method for obtaining the sample meets the criterion of randomness (each element having an equal chance at each draw).
Analog signals can be represented by finite rate discrete samples (uniform, nonuniform, or random) if the signal has some sort of redundancies such as band-limitedness, finite polynomial representation (e.g., periodic signals that are represented by a finite number of trigonometric polynomials), and nonlinear functions of such redundant functions [48, 49].
An observation is missing at random if the probability of missingness depends on the observed data.
The error structure is independent (sometimes termed random) if the off diagonal terms of the auto-correlation matrix are zero.
Inactivation was considered to be random if the ratio of active to inactive X was less than 75:25.
An observation is missing completely at random if the probability of missingness is independent of any observed or unobserved measurements.
Similar(52)
The spatial distribution of infections is considered evenly dispersed if the observed K function values are below the lower limit of the 95% CI, clustered if above the upper limit, or random if within the 95% CI.
Still, it's a lot of power in the hands of randoms: If the jury penalizes Samsung for making their phones and tablets a copy of Apple's then Samsung will need to find a new look.
LMP estimates are prone to large random measurement errors that may become non-random if the exposures under study affects menstrual bleeding patterns.
within-cluster random effects If the LMM/GLMM describes observed random subclusters of size n (with ) and is a cluster-varying covariate with random effect, then and are the mean and variance of the within-observed-cluster effect of.
Functional would best describe it – and random, if you consider the occasional sales of trombones and horse blankets.
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CEO of Professional Science Editing for Scientists @ prosciediting.com