All experiments were performed in replicates of three, and results were reported as mean ± standard error of mean (SEM). To evaluate the cytotoxicity of GNPs, the difference between untreated control group and those treated with GNPs was assessed by paired t-test. In addition, one-way analysis of variance (ANOVA) was used to compare the differences between the treatment groups. The α and β parameters of survival curve were calculated with weighted least square regression and SigmaStat statistical software (SPSS Inc., Chicago, IL, USA). In all experiments, the statistical significance was set at P≤0.05.
Sigmastat statistical software
Manufactured by IBM
Sourced in United States, France
SigmaStat is a statistical software package developed by IBM. It provides a range of statistical analysis tools and functionalities to analyze data and perform various statistical tests. The core function of SigmaStat is to enable users to conduct statistical analyses, such as regression, ANOVA, and hypothesis testing, on data sets.
Automatically generated - may contain errors
Lab products found in correlation
20 protocols using sigmastat statistical software
1
Cytotoxicity Evaluation of Gold Nanoparticles
2
Biochemical Evaluation of Kidney Function
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Biochemical measurements of thawed urine and plasma samples were taken with an automated spectrometric system (Konelab 20 from Thermo Electron Corporation, Cergy-Pontoise, France) and the manufacturer’s biological chemistry reagents and protocols. For the purposes of diagnosing kidney failure, some biochemical and clinical parameters were measured in urine, including volume/24 h, albumin, chlorine, creatinine, glucose, magnesium, potassium, sodium, total proteins, urea, and uric acid. Creatinine and urea were measured in plasma. Creatinine clearance was calculated to estimate the glomerular filtration rate. Biochemical and clinical parameters are reported as the means ± the standard error of the mean (SEM). Statistics were performed with SigmaStat statistical software (SPSS, Paris, France) to calculate items such as Student’s t-test in normal populations or the rank sum test in non-normal populations in order to compare the control and contaminated groups. Statistical significance was defined by a p-value less than 0.05.
3
Statistical Analysis of Research Data
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Statistical comparisons of data were carried out by the Student's t test when the data complied with the conditions of normality and equal variance. Under other conditions, comparisons were done by nonparametric analysis using the Mann-Whitney rank sum test. Probability values of P < .05, determined from two-sided tests, were considered significant. The statistical analysis was performed by using the SigmaStat statistical software (SPSS Science, Chicago, IL).
4
Statistical Analysis of Experimental Data
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Statistical comparisons of data were carried out by the Student’s t test when the data complied with the conditions of normality and equal variance. Under other conditions, comparisons were done by nonparametric analysis using the Mann–Whitney rank sum test. The Kolmogorov-Smirnov method was used to test for normality, and the Levene’s test was used to test for equal variance. Probability values of P < 0.05, determined from two-sided tests, were considered significant. The statistical analysis was performed by using the SigmaStat statistical software (SPSS Science, Chicago, IL, USA).
5
Statistical Analysis Methods for Survival
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The Spearman rank order test was used to search for correlations between parameters. Comparisons of survival curves were performed using the log-rank test. Comparisons of other data sets were conducted using the Student’s t test when the data complied with the conditions of normality and equal variance. Under other conditions, comparisons were carried out by non-parametric analysis using the Mann–Whitney rank sum test. Probability values of P < 0.05 were considered significant. Statistical analysis was performed using the SigmaStat statistical software (SPSS, Chicago, IL).
6
Statistical Analysis for Biological Experiments
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The SigmaStat statistical software (SPSS, Inc., Chicago, IL, USA) was utilized for thorough statistical analysis in this study. Each experiment was replicated a minimum of three times, covering both biological and technical replications. Results are depicted as means ± standard error of the mean. Before analysis, all data underwent normality and homoscedasticity assessments. To identify significant differences among three or more groups, the Kruskal–Wallis test (for non-normally distributed data) and one-way ANOVA (for normally distributed data) were performed. Post hoc analysis for one-way ANOVA entailed Duncan’s multiple range test (for equal variance) or Dunnett’s T3 test (for unequal variance). When comparing two groups, the Mann–Whitney U test (for non-normally distributed data) and Student’s t-test (for normally distributed data) were applied. A significance threshold of p < 0.05 was considered. Additionally, the data were reassessed, and visual representations were generated using GraphPad PRISM 5.01 (PRISM 5, GraphPad Software, USA).
7
Statistical Analysis of Experimental Data
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Statistical comparisons of data were carried out by the Student's t test when the data complied with the conditions of normality and equal variance. Under other conditions, comparisons were done by non-parametric analysis using the Mann-Whitney rank sum test. The Kolmogorov-Smirnov method was used to test for normality, and the Levene's test was used to test for equal variance. Probability values of P < 0.05, determined from two-sided tests, were considered significant. The Pearson product moment correlation test was used to search for correlations between two parameters. The statistical analysis was performed by using the SigmaStat statistical software (SPSS Science, Chicago, IL, USA).
8
Statistical Comparisons in Research
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Statistical comparisons of data were carried out by the paired Student's t test when the data complied with the conditions of normality and equal variance. Under other conditions, comparisons were done by nonparametric analysis using the Mann-Whitney rank sum test. Probability values of P < 0.05 were considered significant. The statistical analysis was performed by using the SigmaStat statistical software (SPSS Science, Chicago, IL).
9
Statistical Analysis of Experimental Data
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Statistical comparisons of data were performed by one-way analysis of variance followed by the Student-Neuman-Keuls test when the data complied with the conditions of normality and equal variance, and under other conditions by the Kruskal-Wallis one-way analysis of variance on ranks. Statistical comparisons of survival curves were performed using the log-rank test. Probability values of P < 0.05 were considered significant. Statistical analysis was performed with SigmaStat statistical software (SPSS, Chicago, IL).
10
Statistical Analysis Methods for Correlations
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The Pearson product moment correlation test was used to search for correlations between parameters. Statistical comparisons of data were carried out with the Student t test when the data complied with the conditions of normality and equal variance. Under other conditions, comparisons were carried out by nonparametric analysis using the Mann-Whitney rank-sum test. The Kolmogorov-Smirnov method was used to test for normality. Probability values of P < 0.05, determined from two-sided tests, were considered significant. The statistical analysis was performed by using the SigmaStat statistical software (SPSS Science, Chicago, IL, USA).
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