Pearson's chi-square test

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Pearson's chi-square test

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Contingency table analyses using the Chi-square statistic were used to determine whether the reasons for use and non-use were independent of the descriptive variables mentioned above.
As shown in Table 2, the Wald chi-square statistic for the joint effect of the inspection variables is only 2.
Pearson's chi-square statistic was employed (it is commonly used to test for homogeneity of groups).
The table presents the percentage of users and nonusers indicating each application, as well as the chi-square statistic for statistically significant difference between the responses of users and nonusers.
LM Chi-Square Statistic for Serial Correlation with 12 lags is 9.
Another evaluation method is to compute a chi-square statistic based on the frequency counts of p-values among bins.
An investigation of the restraints with respect to sample size commonly imposed on the use of the Chi-square statistic.
The most common goodness-of-fit index is the chi-square statistic and its associated p-value.
However, the chi-square statistic indicates that the model is globally significant.
The test is based on Chi-square statistic with degree of freedom equal to the number of excess instruments (i.
Additionally we compute the nonparametric Chi-Square statistic to determine the P-value as well.