All data are expressed as mean ± standard error (SE). Changes between groups were evaluated utilizing a Student t-test and a one-way analysis of variance (ANOVA). Data analysis was performed with SigmaPlot ver. 14.0 statistical software. Differences were considered statistically significant at p < 0.05.
Sigmaplot ver 14
Manufactured by Merck Group
SigmaPlot ver. 14.0 is a scientific graphing and data analysis software application developed by Systat Software, Inc. It is designed to create high-quality graphs and perform advanced data analysis. The software provides a range of features for data visualization, statistical analysis, and curve fitting.
Automatically generated - may contain errors
Lab products found in correlation
5 protocols using sigmaplot ver 14
1
Evaluating Statistical Significance in Research
2
Comparative Bacterial Culture Analysis
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All experiments were performed with two independent bacterial cultures. Data are expressed as means ± standard deviations (SD), and significances of differences were determined using the two-tailed t-test. Statistical significance was accepted for P-values ≤ 0.05 unless otherwise stated. Graphs were prepared using Sigma Plot Ver. 14.0.
3
Bacterial Growth Optimization Protocol
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All experiments were performed using at least two independent bacterial cultures in triplicate. Data represent means ± SD. Statistical validation was performed using the Student’s t test under the assumption of a null hypothesis, and p ≤ 0.05 were considered as significant. Graphs were plotted using Sigma Plot Ver.14.0.
4
Gene Expression Analysis Using 2^-ΔΔCt
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The relative expression of individual genes was analyzed using the 2–ΔΔCt method (Livak and Schmittgen, 2001 (link)). All experiments were performed in triplicate, and statistical analysis was performed using JMP (ver.12) or Sigmaplot (ver. 14) software with α = 0.05. Raw bacterial counts were log-transformed, and log reductions were determined by subtracting the populations of bacteria recovered after treatment from untreated controls. One-way ANOVAs coupled with Tukey’s HSD post-hoc tests were used to determine significant differences in viable cell counts, ROS levels, relative gene expression, and cofactor levels among the treatment conditions.
5
Chlorine Dioxide Disinfection Efficacy
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All experiments were performed in biological triplicate (n = 3) and statistical analysis was performed using JMP (ver. 12) or Sigmaplot (ver. 14) software with α = 0.05. Log reductions of bacteria were determined by subtracting the populations of bacteria recovered after treatment from untreated controls. One-way ANOVAs coupled with Tukey’s HSD post hoc tests were used to determine significant differences among the treatment conditions for each assay. Spearman’s rank correlation coefficients between the results of each assay after ClO2 treatment were calculated using the linear regressions found for each concentration over the time points.
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