SPSS 15.0 package software was used for statistical analyses. Independent samples t-test, chi-square test, and Fisher’s Exact test were used to evaluate the findings, with p values <0.05 were accepted as statistically significant.
Spss 15.0 package
Manufactured by IBM
Sourced in United States
SPSS 15.0 is a software package designed for statistical analysis. It provides a range of tools for data management, analysis, and presentation. The core function of SPSS 15.0 is to enable users to perform a variety of statistical procedures, including regression analysis, hypothesis testing, and data exploration.
Automatically generated - may contain errors
Lab products found in correlation
7 protocols using spss 15.0 package
1
Statistical Analysis of Research Findings
2
Non-Parametric Statistical Analysis
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Data were analyzed by using SPSS 15.0 package software. As the assumptions of parametric tests could not be fulfilled, Kruskal Wallis, Mann-Whitney U test, and Chi-square tests were used for statistical evaluation. A P value of <0.05 was considered to be significant.
3
Analysis of Non-Normally Distributed Data
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For data analysis, the SPSS 15.0 package program was used, and sociodemographic characteristics were calculated as frequency and percentage. To determine the data’s suitability to normal distribution, the Shapiro-Wilk test/Kolmogrov-Smirnov (K-S) (p<0.05) test was performed. Since the data did not show suitability to normal distribution, the Mann-Whitney U test and the Kruskal-Wallis test were used.
4
Statistical Analysis of Research Data
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All statistical analyses were performed with Statistical Package for Social Sciences (SPSS) 15.0 Package (SPSS Inc., Chicago, IL, USA). Descriptive statistics were presented as a mean ± standard deviation. Results that do not show normal distribution are expressed as median (range) values. The Kolmogorov-Smirnov test was used for normality tests. The mean difference between the groups was assessed by Student’s t-test and Mann-Whitney U test. c2 and logistic regression were used for the analysis of categorical data. Relationships between variables were tested using Pearson and Spearman correlation analysis. ROC curve graphs were used to compare sensitivity and specificity. P values less than 0.05 were considered significant.
5
Statistical Analysis of Experimental Data
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The data were expressed as the mean±standard deviation (SD). Statistical comparisons were performed using the appropriate ANOVA model with Duncan post-hoc tests. Differences with p<0.05 were considered significant. The SPSS 15.0 package for Windows was used for the statistical analysis.
6
Diagnostic Value of KRAS and CEA in Mucinous Cysts
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The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and diagnostic accuracy of KRAS, CEA and their combination for the diagnosis of a mucinous cyst were calculated. The true positivity and false positivity was accepted with the positivity of one of the tests. Receiver-operator curves were generated and the area under the curve (AUC) calculated for diagnostic value of the tests. AUC values of tests and their combinations were compared statistically. Comparisons between categorical variables were tested with Chi Square test. Independent Student t-test was used to compare mean values between two independent groups. The agreement between CEA and KRAS to differentiate mucinous cysts was measured by concordance correlation coefficient. An rc value of 1 represents perfect agreement and 0 represents the agreement expected from chance. A 2-tailed P value < 0.05 was considered statistically significant. SPSS 15.0 package program (2006 SPSS Inc., Chicago, IL) was used for statistical analysis.
7
Comparative Statistical Analysis Protocol
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