All data were analyzed for statistical significance with the SPSS17.0 Package (SPSS, US). All numerical data are presented as the mean ± SEM (standard error of mean). p values less than 0.05 were considered significant. All graphs were generated with Graph Pad Prism 5.0 (Graph Pad Software, US).
Spss 17.0 package
Manufactured by IBM
Sourced in United States
SPSS 17.0 is a statistical software package developed by IBM. It provides tools for data analysis, data management, and data visualization. The software is designed to help users analyze and interpret data quickly and efficiently.
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Lab products found in correlation
20 protocols using spss 17.0 package
1
Statistical Analysis of Experimental Data
2
One-way ANOVA Analysis with SPSS 17.0
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The one‐way ANOVA with the SPSS 17.0 package for Windows (SPSS, Inc., Chicago, IL) was used for statistical analysis in this work. The data were expressed as mean ± SE. Differences of P < 0.05 were considered statistically significant.
3
Statistical Analysis of Protein Expression
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Normality of quantitative variables distribution was assessed by Shapiro Wilk test when the sample size was under 30 and Kolmogorov-Smirnov test when the sample size was over 30. The significance of the relationship between two variables with more than two categories (difference between protein expression in three stages of BE) was analyzed with χ2 test. Statistical significance between two binary variables (differences in protein expression between two proteins) was analyzed with Fisher exact test. Correlations between the variables were tested using Phi correlation analysis for binary outcomes and Spearman ρ correlation analysis. Statistical significance of between-group differences for non-normally distributed variables was assessed using Mann-Whitney U test. We used two-sided significance tests in all cases, with the level of statistical significance set at 0.05. All statistical analyses were performed using SPSS 17.0 package (SPSS Inc., Chicago, IL, USA owned by Biometrika Healthcare Research).
4
Comparative Analysis of Rat Protocols
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The parameters were compared among the groups with ANOVA and the Mann-Whitney U test using the SPSS 17.0 package (Chicago, IL, USA) for personal computers. A value of P < 0.05 (two-tailed) was regarded as significant. Different rats were used for each protocol (n = 8 for each protocol). The results represent the mean ± SE of the experiment values.
5
Statistical Analysis of Demographic Factors
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For statistical analysis, the mean values and standard deviation (SD) for age and BMI were calculated using a t-test for paired samples. Regarding gender, education, and marital status, frequency and percentage values were calculated in the T0 period. For questions concerning feelings about weight and body size, ANOVA was applied. For the other instruments, the data were codified according to the specific recommendation instrument, proceeding to statistical treatment using ANOVA, too. All of the statistical analyses were performed using the SPSS 17.0 package. p<0.05 was considered statistically significant.
6
Hardy-Weinberg Equilibrium Assessment
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Hardy-Weinberg proportions (HWE) were tested in controls. Statistical analyses were performed by using the SPSS 17.0 package (SPSS Inc, Chicago, IL). Allelic and genotypic frequency comparisons were analyzed using the χ2 test of a Fisher exact test (when expected values were below 5). Odds ratio (ORs) were calculated and their 95% CIs were estimated with the Cornfield method. Power calculations were performed by using the statistical software package Statcal Epi Info v.6.
7
Longitudinal Analysis of Biomarkers
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Categorical variables were assessed as counts and percent frequency and compared using the chi-squared test. The data were checked for normality using the Kolmogorov-Smirnov test for continuous variables. Normally distributed variables were compared across different time points (T0, T1, T2, and T3) using one-way analysis of variance (ANOVA) followed by post hoc Newman-Keuls tests. Skewed variables were analyzed using the nonparametric Kruskal-Wallis test followed by post hoc Tukey's test. Analysis of covariance (ANCOVA) was used to adjust for potential confounders. All statistical analyses were performed using the SPSS 17.0 package (SPSS Inc., Chicago, IL, USA). A two-tailed P value < 0.05 was considered statistically significant. Owing to the exploratory nature of the study, Bonferroni's correction was not applied.
8
Statistical Analysis of Experimental Data
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Data are presented as mean ± SD. All the data were analyzed by one-way ANOVA followed by Fisher’s-multiple range test or chi-squared test, using the SPSS 17.0 Package (SPSS Inc., US). A p value < 0.05 indicated statistical significance.
9
Statistical Analysis of Research Data
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SPSS 17.0 package was used for statistical analyses. Parameters were expressed in mean ± standard deviation (x ± s) using repeated measures analysis of variance. When the spherical test condition (α = 0.1) was unsatisfied, Greenhouse-Geisser adjustment was applied. Paired t test or paired rank sum test method were used for the self-comparison in each time point. T test or rank sum test method was used for the comparison of the changes of parameters with the significance level of P < 0.05. Sigmaplot 10.0 software was used for plotting.
10
Sociodemographic Factors in Mental Health
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The statistical analysis of sociodemographic variables related to age and BMI were
performed using median and standard deviation. Statistical treatment was proceeded
applying the t-test for independent sample aimed to verify the difference between the
genders. The categorical data was presented by the frequency and percentage. The data
related to the BDI, BAI and BES instruments were codified in accordance to the
specific recommendation of each one of them, continuing the statistical treatment
applying the Chi-square test. In order to compare the results in BDI, BAI and BES
with the normative sample t-test was done. All of the statistical analyses were
performed using the SPSS 17.0 package. p-values <0.05 were considered
statistically significant.
performed using median and standard deviation. Statistical treatment was proceeded
applying the t-test for independent sample aimed to verify the difference between the
genders. The categorical data was presented by the frequency and percentage. The data
related to the BDI, BAI and BES instruments were codified in accordance to the
specific recommendation of each one of them, continuing the statistical treatment
applying the Chi-square test. In order to compare the results in BDI, BAI and BES
with the normative sample t-test was done. All of the statistical analyses were
performed using the SPSS 17.0 package. p-values <0.05 were considered
statistically significant.
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