Significados de categorical data em inglês

Chi-squared tests were used to compare categorical data in different groups.

Student's t-test and Chi-squared test were used to compare continuous and categorical data, respectively.

Student's t-test and chi-square analysis were used to assess continuous and categorical data, respectively.

Comparisons were done with T-tests for continuous data and Chi-square tests for categorical data.

Methods: Phenotypes used in this study were categorical data.

The chi2 test was used to compare categorical data.

Main outcome measure: chi 2 Test for qualitative data and Student t test for categorical data.

Student t test and Pearson chi-square test were used for continuous and categorical data analyses, respectively.

All categorical data was analyzed using chi-square analysis.

We assessed the psychometric properties of the migraine screen questionnaire (MS-Q) using categorical data methods.

Whereas for categorical data, percentages were calculated.

The performance of three such methods-BayesianClassification, Hypergraph-BasedClustering, and Fuzzy k-ModesClustering-appropriatefor categorical data were compared.

Univariate analysis with chi-squared tests for categorical data and t tests or ANOVA tests for continuous data was used.

Statistical analysis was powered by standard software expressing categorical data as numbers and percentages and quantitative data as means ±standard deviations.

Numerical data were reported using the Kruskal-Wallis and Wilcoxon sum rank tests and categorical data compared using the two-sample test of proportions.

Mann-Whitney U-test for continuous non-parametric variables, independent paired t test for continuous parametric variables and chi-square test for categorical data were used.