chi-square test


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chi-square test

 
a statistical procedure for determining significant differences between frequencies observed within the data and frequencies that were expected. There are two chi-squared tests: the chi-square test of independence, which tests whether two or more series of frequencies are independent of one another; and the chi-square test of goodness of fit, which tests whether an observed frequency distribution fits a specified theoretical model. Written also χ2-test.

chi-square test

a statistical method of assessing the significance of a difference, as when the data from two or more samples, such as the numbers of females and males attending each of two colleges, are represented by a discrete number.
Synonym(s): χ2 test
References in periodicals archive ?
The Pearson Chi-square test shows that there is no association between the two variables, involvement of female employees in key decision making bodies and gender as the value of significance is .
Using dichotomized performance scores, (a) less than proficient and (b) proficient or above, a chi-square test of independence found a dependency between the performance of students who took the 2009 AA-MAS math assessment and their prior performance on the 2008 general math assessment, [chi square](1) = 13.
1) Arrival patterns of vehicles were fitted as the Poisson distribution and chi-square test analysis validated the likelihood of field values conforming to the proposed distribution.
Frequency results used in chi-square test for independence for level of technology adoption versus 5-year revenue change.
Possible gender effect on self-esteem scores was examined by the chi-square test of independence.
Table 1: Perception Regarding Perceptually Weak Areas STATE/UT Total Punjab Haryana HP Chandigarh Perceptually Planning 20 31 10 5 66 weak areas Organizing 18 22 7 7 54 Controlling 37 22 33 13 105 Total 75 75 50 25 225 Chi-Square Test Calculated Value Degrees of Freedom Tabulated Value Pearson Chi-Square 18.
The Chi-square test showed that differences between the two decades were statistically significant for five variables: jurisdiction; industrial category; occupational category of the complainant; complainant's visible minority; group; and the complainant's formal relationship with the alleged discriminator.
If the results for effects of testing order and sex were not significant, I then pooled the data and tested various hypotheses concerning prey choice using a Chi-square test for goodness-of-fit or independence as appropriate.
The results of the Chi-square test did not, however, provide any statistical relationship between the size of firm, amount of experience and education of estate surveyors and valuers and their perception on the comparative importance of the identified clients' influencing factors.
A chi-square test revealed that the total number of descriptions of "improved" were significantly more than those of "unimproved.
Comparisons of above criteria were made between the two groups using chi-square test or Fischer's exact test.