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Table 3 below shows results of the chi-square test ([chi square]).
In our study, we verified using the Chi-square test of independence that the sample type, serogroup, and PFGE pattern are closely correlated.
The Pearson Chi-square test shows that there is no association between the two variables, providing mentors to employees and gender, as the value of significance is .
The Cox proportional hazards model considered servicemembers who were not discharged during the 2 yr follow-up as censored observations, with censoring dates equal to 2 yr postamputation, and we used a 1-degree of freedom (DOF) Wald chi-square test to assess the relationship between TBI status and survival.
A chi-square test of independence found a dependency between performance on the 2008 general reading test and performance on the 2009 AA-MAS reading test, [chi square](1) = 14.
Chi-square test shows that we cannot reject the null hypothesis that residuals are Irrelevant.
Chi-square test was done to find out the significance of the OR.
The chi-square test was performed to assess the goodness-of-fit of field observed data as the Poisson distribution.
The analysis set was comprised of 570 patients, whose biopsy rates, positive predictive values (PPVs) of biopsy, and overall cancer yields were calculated and compared using the chi-square test across patient age, breast density, index tumor type, receptor status and lymph node status.