Sentence examples for independence of variables from inspiring English sources

Here, we show the effect of independence of variables on the utility functions and later consider dependence and independence of variables in the examples of Sect. 3.

Classical tolerance design procedures are based on the assumption of independence of variables.

Independence of variables is determined by whether or not another variable is a direct descendent in the DAG representation [47].

Illustrative examples considering dependence and independence of variables are worked through to demonstrate the usefulness of the proposed model.

The usefulness of the approach was illustrated by working through an example in two cases of dependence and independence of variables.

Assuming that the utilities (u_{11}, ldots,u_{{1,p_{i} }}) corresponding to the ith objective function are incompatible with one another, the probability of the utilities in conditions of dependence and independence of variables is considered separately and then the total probability and sum of probability rules are used.

By placing the most confidence on multivariate tests that take into account the non-independence of variables, the strongest results emerged from analyses of the effects of population size with all four measures of taxonomic richness (ischnoceran, amblyceran, overall species richness and genus richness).

The emphasis in this section is mainly on introducing some concepts such as credibility measure, credibility space, fuzzy variables, independence of fuzzy variables, expected value, variance, fuzzy process, Liu process, and stopping time.

As defined, statistical independence of two variables means that the occurrence of one variable makes it neither more nor less probable that the other occurs.

Statistical independence of two variables probabilistically means that the occurrence (value) of one variable does not change the probability for that (value) of the other.

The chi-squared (χ 2) statistic is used to test the independence of two variables by computing a score to measure the extent of independence of these two variables.