The second major reliability statistic is the standard error of measurement. The Standard error of measurement is a function of the coefficient of reliability and the degree to which the scores on a test tend to spread out around the average score (O’Connor and Kleyner, 2012).
Correlation and Dependence
Dependence defines to the statistical relationship between 2 data sets or random variables whereas correlation defines wide number of statistical relationships by managing dependence. Dependence also defines to any situation in which random variables do not satisfy the probabilistic dependence of mathematical condition. Whereas correlation can also be referred to the more than 2 random variables departure from independence, but technically defined several specialized kinds of relationship between mean values Correlation is an association measure whereas dependence is the absence or presence of a relationship between variables measure. Correlation is the appropriate measurement of dependence only for a specific set of joint distributions. If the dependence framework is not described by one of the distributions the estimated or calculated correlation relies not only on the dependence nature but also on the marginal distribution behavior. It follows the stochastic correlation nature which is not driven by the stochastic dependence nature but by the alterations in the marginal behavior. To decide whether to introduce stochastic correlations and other members it will be useful to know whether stable non correlation dependence with differing marginal is dealing or with a genuinely varying framework of dependence (Mari and Kotz, 2001; Eydeland and Wolynesic, 2003, p 234).