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Sigmastat

Manufactured by IBM
Sourced in United States, Germany

SigmaStat is a statistical analysis software designed for scientific and engineering applications. It provides a comprehensive set of statistical tools for data analysis, including regression, ANOVA, t-tests, and nonparametric methods. SigmaStat is designed to be user-friendly and offers a wide range of data visualization options.

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163 protocols using sigmastat

1

Evaluating Nonparametric Statistical Methods

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Data are presented as median (IQR, interquartile range) and were analyzed with the Wilcoxon Signed Rank Test (Sigma-Stat, SPSS, Chicago, IL, USA) after having passed the Friedman Test (Sigma-Stat, SPSS). p values of ≤0.05 were considered significant.
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2

Comparative Analysis of Cell Responses

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Data were presented as mean ± standard deviation (SD), and analyzed with the Wilcoxon-Signed-Rank-Test (Sigma-Stat, SPSS, Chicago, IL, USA) after passing the Friedman-Test (Sigma-Stat). p-values ≤ 0.05 were considered significant. All analyses in the static cell culture were done with six different cultures in quadruplicate. The amount of experiments in the dynamic setting was specified in the respective data presentation.
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3

Quantification of Methylated DNA by QMSP

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MTT assay results were quantified using SoftMax® Pro software (Molecular Devices, LLC). The methylated intensity ratio of QMSP was determined as the percentage of methylated reference (PMR), and the PMR value was defined as: [(ADHFE1)sample/(ACTB)sample]/[( ADHFE1)M.SssI/(ACTB)M.SssI] × 100. A PMR value of ten or more indicated hypermethylation. The significance of the differences in PMR values was defined by the chi-squared test, Fisher’s exact test, and ANOVA using Sigma Stat (SPSS Inc., Chicago, IL, USA). In all statistical tests, p-Values of < 0.05 were considered statistically significant. Real-time PCR and immunoblot analysis data were compared and qualitative differences between samples were analyzed using Sigma Stat (SPSS Inc.). p-Values of < 0.05 were considered statistically significant.
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4

Comparative Analysis of Platelet-Endothelial Interactions

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Data were presented as mean AE standard deviation (SD). Due to non-normality of the data, the Wilcoxon-Signed-Rank-Test (Sigma-Stat, SPSS, Chicago, IL) was used after passing the Friedman-Test (Sigma-Stat, SPSS, Chicago, IL). p-Values 0.05 were considered significant. All analyses in the static cell culture were done with six EC and five platelet donors. Other details see text.
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5

Comparative Statistical Analysis of Treatments

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All statistical analyses were performed using SigmaStat (SPSS Inc., Chicago, IL) with an error rate set at α = 0.05. The significance difference between treatments was tested using Tukey's Honestly Significant Difference Test.
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6

Electrophysiological Assessment of LTP

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Data were analyzed offline using software from Spike 2 (CED, Cambridge, UK). LTP was expressed as the PSP slope and normalized to the average PSP slope over the last 10 min before LTP induction.
All statistical tests were performed using SigmaStat software (SPSS Inc., California, USA). Data sets were tested for normality using the Shapiro–Wilk test, but no deviation from a normal distribution was detected and results are expressed as mean ± standard error of mean. Comparison of HFS‐induced plasticity was performed between groups using two‐way repeated‐measures ANOVA. This analysis was followed by a post hoc t‐test performed between groups. Differences between groups and changes within groups were considered statistically significant if P < 0.05.
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7

Statistical Analysis of Experimental Data

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Statistical analysis was performed using Statistical Package for the Social Sciences, Version 11.0 for Windows (SigmaStat, SPSS Science, Chicago, IL, USA). Data were collected from at least six parallel samples. The results were reported as the mean ± standard deviation (SD). Values were considered to be significant at p < 0.05.
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8

Comparing Growth Factors in PCOS

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A power analysis powered for a two-tailed t-test was carried out prior to subject enrollment to determine the minimum required sample sizes needed to detect a 1.5-fold (assumed) statistically significant difference in growth factor between cases (PCOS) and controls. The required level of significance was at least 95% (p = 0.05), and the required power of the test was at least 90% (p = 0.10). Based on this calculation the required sample sizes were n = 14 for each group. Data were analyzed by Student’s t-test or the Mann–Whitney test, as appropriate. Results are expressed as mean +/- standard error of the mean (SEM). Correlations between PlGF or sFlt-1 and various parameters were performed using Pearson correlation tests. SigmaStat (SPSS Science, Chicago, IL) was used for statistical analysis. All significance tests were two-tailed and P-value <0.05 was considered to be statistically significant.
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9

Statistical Analysis of Biological Data

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All statistical analysis was performed using SigmaStat (version 13, SPSS, Chicago, IL). Data are presented as means ± SEM for both absolute values and percent change relative to individual baseline. Any data points that were more than 2 standard deviations from the mean values were designated as outliers and removed from analysis. For multiple group comparison, we used repeat measures 2-way ANOVA with the Holm-Sidak method post hoc analysis where appropriate. Values of P ≤ 0.05 were considered statistically significant. All plots were created using Prism (GraphPad, San Diego, CA).
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10

Statistical Analysis of Genotype and Diet Effects

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All data were analyzed, using commercial software (SigmaStat, SPSS, Chicago, IL). All outcomes were analyzed using a two‐way ANOVA (genotype x diet), except for PPARγ western blot analysis, which was analyzed by a Two‐Tailed Student's t‐Test. Student–Newman–Keuls test was used for all post hoc analyses. Any data that were not normally distributed or did not display equal variance were logarithmically transformed so that these criterion were met. Statistical significance was set with an alpha value of P < 0.05. Data are presented as mean (±SEM).
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