chi square

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chi square (c2)

a statistical test for use with nominal data (see CRITERIA AND LEVELS OF MEASUREMENT). The EXPERIMENTAL HYPOTHESIS predicts how many subjects in each group being tested will fall into certain categories if there are no differences between the groups, and the chi-square test compares the observed frequencies with the expected frequencies. The larger the difference between the observed and expected frequency, the more likely that there is a statistically significant difference between the categories.
Collins Dictionary of Sociology, 3rd ed. © HarperCollins Publishers 2000
References in periodicals archive ?
Chi square and exact tests were also performed to find out significant difference between parity categories of cohort 'A' and cohort "B'.
Then it was organized, tabulated and analyzed through percentage and chi square. A statement was supported, when the chi-square value was found greater than the table value of 3.841 at the 0.05 level of significance and was not supported when found lesser than the table value.
To indicate the direction of the relation between a form and a class (in Table 1, e.g, whether there were, or not, more Form 1 present in Class 1 than in the other classes, or vice versa), the sign of the difference between the observed and the expected frequencies is added to the chi square value, which is then denominated chi square of association.
If the Rasch model package computes Andersen's LR test then the statistic can easily be computed by dividing the chi square value by its associated degrees of freedom.
The greater chi square value X2 pless than 0.05, df (1) = 4.66 also shows that our hypothesis about this belief is accepted.
However, what appears counter intuitive is that Chi Square is less robust and more blunt and yet can cover more numerical territory.
Data were analysed using both descriptive and inferential statistics which include frequency counts, percentages, and hypothesis test using chi square at P<0.05.
Comparisons of categorical variables were conducted with Chi Square ([chi square]) analysis and of interval/ratio variables with one-way analysis of variance (ANOVA) with Scheffe tests for post-hoc comparisons.
Results of a 2 X2 Chi Square test revealed that 46.3.% of males chose physical attractiveness as a significant factor when choosing a long term mate in comparison to 37.5% of the females ([chi square] = 4.501; p=.034).
Reincarceration: Served Out and Paroled Groups ATTRIBUTE SERVED PAROLED OUT Reincarcerated 40.5% 62.8% Reincarceration New offense 35.5% 1 1.8% Return to 4.0% 51.0% prison(Recommitment or parole violation) Reincarceration Offense (1) (New Crime Only) Drug 36.9% 46.1 % Violent 12.2% 12.7% Property 9.8% 9.4% Theft 15.9% 15.4% Other 25.2% 16.4% (1) Chi square value: 46.63, degrees of freedom = 4, p =.000 Discussion
In the case of sex, the Chi square tests indicate significant differences in the academic context [[chi square](5, N = 522) = 13.48,p <.05] but not in the leisure context [[chi square] (5, N = 522) = 7.70, p >.05].