Common use of Statistically significant differences Clause in Contracts

Statistically significant differences. Large sample sizes may inflate measures of statistical significance and may lead to false conclusions about the strength of association. The chi-square measure of association, in particular, is susceptible to this possibility. Therefore, the standards for designating whether a relationship can be termed statistically significant have been increased: the Xxxxxxx’x xxx-square must have probability of a type 1 error of less than .001 and either the Phi coefficient or Xxxxxx’x V must have a value of .150 or greater. Throughout this document, any differences reported meet these criteria, unless otherwise stated. Xxxxxxx’x xxx-square <.001 Phi coefficient or Xxxxxx’x V .150 or higher Non-responses have not been included in the analysis. Therefore, throughout this report, unless explicitly stated as a subpopulation, overall results exclude those who did not respond to a particular question.

Statistically significant differences. Large sample sizes may inflate measures of statistical significance and may lead to false conclusions about the strength of association. The chi-square measure of association, association in particular, particular is susceptible to this possibility. Therefore, the standards for designating whether a relationship can be termed statistically significant have been increased: the Xxxxxxx’x xxx-square must have probability of a type 1 error of less than .001 and either the Phi coefficient or Xxxxxx’x V must have a value of .150 or greater. Throughout this document, any differences reported meet these criteria, unless otherwise stated. Xxxxxxx’x xxx-square <.001 Phi coefficient or Xxxxxx’x V .150 or higher Non-responses have not been included in the analysis. Therefore, throughout this report, unless explicitly stated as a subpopulation, overall results exclude those who did not respond to a particular question.