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Statistical package for social science 20

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Statistical Package for Social Science (SPSS) 20.0 is a comprehensive software suite designed for statistical analysis. It provides a wide range of tools and features for data management, analysis, and visualization. SPSS 20.0 is primarily used for statistical modeling, surveys, and research in the social sciences.

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Access 2010, by IBM (1 mentions)

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Statistical Packages for the Social Sciences version 20.0 (2 citations)

4 protocols using statistical package for social science 20

1

Comparative Analysis of ASD and Control

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All demographic and clinical variables were subjected to statistical analysis. Descriptive analysis was conducted for sociodemographic variables featuring the two samples (ASD and control groups). To compare the gender between the ASD and control groups, we used the Fisher’s exact test. Student’s t-test was used to examine the differences in age, NAA/Cr (mean value), and Cho/Cr (mean value) between the ASD and control groups. In addition, the Student’s t-test was also used to examine the differences in NAA/Cr (mean value) and Cho/Cr (mean value) between children with ASD and children with ASD and cognitive impairment. Statistical significance was considered for a P-value ≤0.05. We used the statistical program Statistical Package for Social Science 20.0.
Margari L., De Giacomo A., Craig F., Palumbi R., Peschechera A., Margari M., Picardi F., Caldarola M., Maghenzani M.A, & Dicuonzo F. (2018). Frontal lobe metabolic alterations in autism spectrum disorder: a 1H-magnetic resonance spectroscopy study. Neuropsychiatric Disease and Treatment, 14, 1871-1876.
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2

Statistical Analysis of Variables

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Mean and standard deviation were determined for each variable studied. Statistical significance was evaluated using one-way analysis of variance (ANOVA) followed by Bonferroni post hoc test for multiple comparisons. For bivariate analysis, Spearman’s correlation coefficient was calculated. All the analyses were performed using Statistical Package for Social Science 20.0 (SPSS, Chicago, IL, USA).
Sánchez-González C., Moreno L., Aranda P., Montes-Bayón M., Llopis J, & Rivas-García L. (2022). Effect of Bis(maltolato)oxovanadium(IV) on Zinc, Copper, and Manganese Homeostasis and DMT1 mRNA Expression in Streptozotocin-Induced Hyperglycemic Rats. Biology, 11(6), 814.
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3

Multivariate Statistical Analysis Protocol

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Results of the analysis were subjected to one-way analysis of variance (ANOVA) and multiple comparisons of means by post hoc Tukey’s procedure by Statistical Package for Social Science 20.0 software (International Business Machines Corporation). The dissimilarity index was calculated using Darwin (6.0.15) software package. Multivariate statistical analyses were carried out using XLSTAT 2018 software (Addinsoft) for Microsoft Excel®.
Boyaci Gunduz C.P., Agirman B., Gaglio R., Franciosi E., Francesca N., Settanni L, & Erten H. (2022). Evaluation of the variations in chemical and microbiological properties of the sourdoughs produced with selected lactic acid bacteria strains during fermentation. Food Chemistry: X, 14, 100357.
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4

Epidemiological Study of Infective Endocarditis

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The data were stored in Microsoft Access 2010 and were analyzed using Statistical Package for Social Science 20.0 (IBMcorp, Chicago, IL, USA). Categorical variables are presented as percentages and were compared using the chi-squared or Fisher's exact tests as appropriate. Continuous variables are summarized as medians and interquartile ranges, and the Mann–Whitney U test was used to evaluate the group differences. Odds ratios (OR) with 95% confidence interval (CI) were calculated using logistic regression. The variables of interest included the epidemiological data, predisposing factors, place of IE acquisition, laboratory tests, and echocardiographic findings as well as the causative pathogens. After univariate analysis, variables with P values less than 0.05 were included in forward stepwise logistic regression to identify independent variables. The site of IE acquisition was included in the regression model as coded dummy variables. P values less than 0.05 were considered statistically significant.
Yang F., Zhang B., Yu J., Shao L., Zhou P., Zhu L., Chen S., Zhang W., Weng X., Zhang J, & Huang Y. (2015). Epidemiology and the prognosis of healthcare–associated infective endocarditis in China: the significance of non-nosocomial acquisition. Emerging Microbes & Infections, 4(7), e38-.
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