Word frequency of selected vocabularies about pandemic influenza preventive measures were collected from the documents and the correlations between the word frequency of these measures were analyzed. In order to reduce the influence of the maximum or minimum of frequency between the vocabularies on the correlation, Ochiai coefficient was employed to show the correlation between the two vocabularies with the calculation formula Ochiai coefficient = , where AB is the frequency of co-occurrence between words A and B; A is the frequency of occurrence of the word A; B is the frequency of occurrence of the word B. The calculation was done by using the software Statistical Product and Service Solutions (SPSS 12.0 for windows, SPSS Inc., Chicago, IL, USA).
Spss 12.0 for windows
Manufactured by IBM
Sourced in United States
SPSS 12.0 for Windows is a statistical software package designed to analyze data. It provides a comprehensive set of tools for data management, analysis, and reporting. The software offers a user-friendly interface and a wide range of statistical procedures, including descriptive statistics, regression analysis, and advanced multivariate techniques.
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80 protocols using spss 12.0 for windows
1
Analyzing Pandemic Influenza Prevention Measures
2
Variance Analysis of Experimental Data
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All experimental data were analyzed by of variance (ANOVA) and significant differences among means from triplicate analyses (p < 0.05) were determined by Duncan’s multiple range tests using the statistical analysis system (SPSS 12.0 for windows, SPSS Inc., Chicago, IL, USA).
3
Statistical Analysis of Experimental Data
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Statistical analysis was performed using SPSS 12.0 for Windows (SPSS Inc., Chicago, IL). Test selection was based on evaluating the variables for normal distribution using the Kolmogorov–Smirnov test. If the variables had a normal distribution, independent t-test was used. If the variable did not have a normal distribution, the analysis was done using the Mann–Whitney U test. To comparison of gender was evaluated by Chi-square test. Statistical significance was chosen as P < 0.05.
4
Effect of Ae/An ratio on CSB properties
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The obtained data in this work were presented as mean ± standard deviation of multiple measurements, and the statistical analysis of data was carried out using the software SPSS 12.0 for Windows. One-way ANOVA was used to analyze the data to ascertain whether the change of Ae/An ratio significantly affected CSB properties. The level of significance of correlation coefficient was analyzed by a two-tailed test.
5
Comparing Heart Rate Reserve and RPE
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All data are reported as mean ± SD. The statistical program SPSS 12.0 for Windows (SPSS Inc., Chicago, IL, USA) was used for statistical analysis. The Kolmogorov–Smirnov test was applied to ensure a Gaussian distribution of the results. Paired Student's t test was used to analyse the differences between interventions (HRRESERVE vs. RPE). The significance level was set at p < 0.05.
6
Statistical Analysis Methodology
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Statistical analyses were performed using a statistical software package SPSS 12.0 for Windows (SPSS Inc., Chicago, IL, USA). When appropriate, results were expressed as proportions, mean±standard deviation, or medians (interquartile range, IQR). Significance was evaluated using the Fisher exact test, independent t-test, Mann-Whitney U-test, and Kruskal-Wallis test. A p<0.05 was considered statistically signficant.
7
Statistical Analysis of Experimental Data
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The statistical analyses were conducted using SPSS 12.0 for Windows (SPSS Inc., Chicago, IL, USA). Student's t-test and Pearson correlation coefficients values were calculated. Null hypotheses of no difference were rejected if p-value were less than 0.05.
8
Factors Associated with SMNF and MONF
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Univariate analysis was used to determine factors associated with SMNF and MONF. An independent Student’s t test was used for numerical data. A χ2 test or a Fisher’s exact test was used for categorical data. Descriptive data are presented as the mean ± standard deviation for quantitative variables and as frequency for categorical variables. Significance was set at p < 0.05. Multivariate analysis was used to determine independent risk factors associated with underlying comorbidities. All factors significant in univariate analysis were included in a multivariate logistic regression analysis. SPSS 12.0 for Windows was used for all statistical analyses.
9
Statistical Analysis of Experimental Outcomes
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Statistical analyses between groups were performed by ANOVA test (SPSS 12.0 for Windows). The Mann-Whitney nonparametric test was used for group-to-group comparison. Bivariate association between quantitative variables was assessed by the Spearman’s correlation coefficient. Statistical significance was defined when p≤0.05. Data are expressed as mean±SEM.
10
Analyzing Experimental Group Differences
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The data are presented as the mean ± standard error of mean (SEM). All statistical analyses were performed using SPSS 12.0 for Windows (SPSS Inc. Armonk, NY, USA). Statistical differences between the experimental groups were assessed by ANOVA, followed by the Turkey-Kramer HSD post hoc test. Different letters indicate significant differences between groups (p < 0.05).
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