Statistically significant differences Sample Clauses

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. Table 5: Criteria for statistical significance Test Level for significance Xxxxxxx’x xxx-square <.001 Phi coefficient or Xxxxxx’x V .150 or higher 1.6 Non-response 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.
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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.
Sample 1Sample 2Sample 3See All (6)
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, we increased the standards for designating whether a relationship can be termed ―statistically significant.‖ The benchmarks shown in Table 5 must be met for us to term an association statistically significant; 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. Table 5: Criteria for statistical significance Test Level required for significance Xxxxxxx’x xxx-square <.001 Phi coefficient or Xxxxxx’x V .150 or higher 1.6 Non-response Unlike previous years, non-responses have not been included in the analysis. Therefore, throughout this report, unless explicitly stated as a subpopulation, overall results do not include those who did not respond to a particular question. However, for questions where ―don’t know‖ is a valid response, overall results include those who selected ―don’t know‖ to a particular question, although they are not always shown in a table. Therefore, responses to some questions may not sum to 100%.
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Related to Statistically significant differences

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