IBM SPSS software package version 20.0 was used for analysis of the collected data. Mean ± standard deviation (SD) was used to express the quantitative data. Frequency and percentage were used to express the qualitative data. When comparing between two means, the independent-samples t-test of significance was used. In order to compare proportions between two qualitative parameters, chi-square (χ2) test of significance was used.
Spss software package version 20
Manufactured by IBM
Sourced in United States
SPSS is a software package developed by IBM for statistical analysis. Version 20.0 features tools for data management, advanced statistics, and visualization. The core function of SPSS is to provide users with a comprehensive set of analytical capabilities to explore and understand data.
Automatically generated - may contain errors
Lab products found in correlation
Prism 5, by GraphPad (4 mentions)
Excel spreadsheet, by IBM (1 mentions)
Prism version 8, by GraphPad (1 mentions)
Statistical software version 18, by MedCalc (1 mentions)
Spss software package, by IBM (1 mentions)
Sep pak c18 cartridge, by Waters Corporation (1 mentions)
Statistical software version 19, by MedCalc (1 mentions)
Trizol ls reagent, by Thermo Fisher Scientific (1 mentions)
Hiscript 2 reverse transcriptase, by Vazyme (1 mentions)
283 protocols using spss software package version 20
1
Statistical Analysis of Collected Data
2
Statistical Analysis of Experimental Data
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Data were fed to the computer and analysed using IBM SPSS software package version 20.0. (Armonk, NY: IBM Corp.). Shapiro–Wilk test was used to verify the normality of distribution of variables; comparisons between groups for categorical variables were assessed using χ2 test (Monte Carlo). Marginal homogeneity test was used to analyse the significance between the different stages. Mann–Whitney test was applied to compare between two groups for not normally distributed quantitative variables. Wilcoxon signed ranks test assessed for comparison between two periods for not normally distributed quantitative variables. ANOVA was used for comparing different categories. Kruskal–Wallis test was used to compare different categories for abnormally distributed quantitative variables. Pearson coefficient was used to correlate between two normally distributed quantitative variables. Significance of the obtained results was judged at the 5% level [67 , 68 ].
3
Comparison of Bacterial Counts in Oral Samples
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Data were fed to the computer and analyzed using the IBM SPSS software package version 20.0. Quantitative data were described using range (minimum and maximum), mean, and standard deviation. A bar chart was used to graphically describe the data. The distributions of the quantitative variables were tested for normality using the Kolmogorov–Smirnov test. It revealed that the data were normally distributed, and the parametric test was applied. A comparison between two independent populations was done using an independent t test; also, the paired t test is used to analyze two paired data. Bacterial counts were transformed to log10 (CFU/mL). The paired t test was used to compare between the two groups in log S. mutans counts and to study the changes by time in each group. The level of statistical significance was set at p ≤ 0.05.
4
Comparison of Nutritional Data Analysis
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Data were fed to the computer and analyzed using IBM SPSS software package version 20.0. (Armonk, NY: IBM Corp). For continuous data, they were tested for normality by the Shapiro–Wilk test. Quantitative data were expressed as a range (minimum and maximum), mean, and standard deviation for normally distributed quantitative variables Paired t-test was used to compare nutritional facts per serving and laboratory nutritional facts per serving. On the other hand, for not normally distributed quantitative variables, Wilcoxon signed ranks test was used to compare nutritional facts per serving and laboratory nutritional facts per serving. The significance of the obtained results was judged at the 5% level24 ,25 (link).
5
Assessing Mediation of Sexual Dysfunction
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Data were fed to the computer and analyzed using IBM SPSS software package version 20.0. (IBM; Armonk, NY). The Kolmogorov- Smirnov test was used to verify the normality of distribution of variables, Comparisons between the 2 periods for categorical variables were assessed using McNemar test, while Wilcoxon signed ranks test was assessed for comparison between 2 periods for abnormally distributed quantitative variables. Significance of the obtained results was judged at the 5% level.
Possible mediation by sexual dysfunction on the association between anxiety/depression and sexual satisfaction was examined. The Preacher and Hayes method23 (link) was used to test the magnitude and significance of mediation.
Possible mediation by sexual dysfunction on the association between anxiety/depression and sexual satisfaction was examined. The Preacher and Hayes method23 (link) was used to test the magnitude and significance of mediation.
6
Statistical Analysis of Categorical Data
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Data were analyzed using IBM SPSS software package version 20.0. Qualitative data were described using number and percentage. Comparison between different groups regarding categorical variables was tested using Chi-square test. When more than 20% of the cells have expected count less than five, correction for Chi-square was conducted using Monte Carlo correction. Significance of the obtained results was judged at the 5% level (11 ).
7
Statistical Analysis of Qualitative and Quantitative Data
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Qualitative data were described using number and percent. Quantitative data were described using range (minimum and maximum), mean, standard deviation, median, and interquartile range (IQR). The significance level of p value was set at 0.05. Chi-squared test and Fisher’s exact (Monte Carlo correction) were applied to assess data between different groups.
Statistical analysis was performed using IBM SPSS software package version 20.0. (Armonk, NY: IBM Corp).
Statistical analysis was performed using IBM SPSS software package version 20.0. (Armonk, NY: IBM Corp).
8
Statistical Analysis of Experimental Data
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Data were fed to the computer and analyzed using IBM SPSS software package version 20.0. ( IBM Corp) . Significance of obtained results was judged at 5% level.
9
Renal Masses Characterization Protocol
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Data were analyzed using IBM SPSS software package version 20.0 (SPSS Inc., Chicago, IL, USA). Qualitative data were described using numbers and percentages. Correlations were calculated using an independent-sample t-test, chi-squared test, and Fisher exact test. P value < of 0.05 was considered statistically significant. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the “angular interface” sign to differentiate benign from malignant lesions were evaluated. A multivariate logistic regression model including patient’s age, mass side and site, maximal dimension, contrast enhancement, presence of angular interface sign, and presence of intralesional fat was used to evaluate for the features associated with the likelihood of benign versus malignant renal masses.
10
Statistical Analysis of Research Data
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Data were fed to the computer and analyzed using IBM SPSS software package version 20.0. ( Armonk, NY: IBM Corp). The Kolmogorov- Smirnov was used to verify the normality of distribution of variables. ANOVA was used for comparing the different studied groups and followed by Post Hoc test (Tukey) for pairwise comparison. Kaplan-Meier Survival curve was used for overall survival. Comparisons between groups for categorical variables were assessed using Chi-square test (Fisher’s Exact or Monte Carlo correction). Significance of the obtained results was judged at the 5% level [30 ].
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