Data were analyzed using STATISTICA version 13.3 program (StatSoft, Inc., Tulsa, OK, USA) and results were express as mean ± standard deviation (SD). The categorical data from repeated measurements were analyzed by variance analysis. To assess the distribution of total nitric oxide, malonyldialdehyde, nitrotyrosine, and asymmetric dimethylarginine data Shapiro–Wilk’s test of normality and visual inspection of Q–Q plots was used. Data revealed a normal distribution, hence we used ANOVA with Tukey’s post hoc test and Student t-test for pairwise comparisons. The relationship between total nitric oxide and its activity indicators was analyzed by Spearman’s rank correlation test. The results were considered significant if p-values were 0.05 or less. The data were plotted using STATISTICA version 13.3 (STATSOFT; Statistica, Tulsa, OK, USA).
Statistica version 13
Manufactured by StatSoft
Sourced in United States, Poland, Czechia, Germany
Statistica version 13.3 is a comprehensive data analysis and statistical software suite. It provides a wide range of analytical tools and algorithms for data processing, modeling, and visualization. The software is designed to handle large datasets and offers capabilities for advanced statistical analysis, machine learning, and predictive modeling.
Automatically generated - may contain errors
Lab products found in correlation
Spss version 25, by IBM (6 mentions)
Version 15, by MedCalc (4 mentions)
Spss version 22, by IBM (4 mentions)
Prism 9, by GraphPad (2 mentions)
Spss version 26, by IBM (1 mentions)
Plus for windows 5, by Statgraphics (1 mentions)
Statistica 13, by StatSoft (1 mentions)
Tablecurve 2d, by Grafiti LLC (1 mentions)
Spss statistics for macintosh version 29.0, by IBM (1 mentions)
Cla methyl esters, by Merck Group (1 mentions)
Spss statistics version 26, by IBM (1 mentions)
Version 12, by MedCalc (1 mentions)
Nsolver 4.0 analysis software, by NanoString (1 mentions)
Ingenuity pathway analysis (ipa), by Qiagen (1 mentions)
Prism 6, by GraphPad (1 mentions)
Originpro 2022, by OriginLab (1 mentions)
Simca 16, by Sartorius (1 mentions)
Spss v24, by IBM (1 mentions)
Prism 9.0 for windows, by GraphPad (1 mentions)
Sigmaplot version 13, by Grafiti LLC (1 mentions)
278 protocols using statistica version 13
1
Oxidative Stress Biomarkers Analysis
2
Comparative Analysis of Beef Quality
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All experiments were performed in triplicate. The results obtained were assessed using statistical methods. Data were analyzed using a three-way analysis of variance (ANOVA) to determine the differences in the physical and chemical properties of beef, which were found to be affected by slaughter type, gender, and muscle type. To determine the effects of these parameters on the quality of the final product, the general linear model procedure was used (ANOVA, STATIST ICA version 13.1; StatSoft, Krakow, Poland) for a fixed effect model with two types of slaughter, two groups of muscle, and two groups of gender. In the case of significant effects (p < 0.05), the average values were compared using Tukey’s post hoc HSD test (ANOVA, STATISTICA version 13.1; StatSoft, Krakow, Poland). The average values and the standard error of mean values of color parameters, texture parameters, and sensory properties of beef samples are summarized in Table 1 , Table 2 and Table 3 .
3
Statistical Analysis of Material Microstructure and Mechanical Properties
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Statistica version 13.3 (StatSoft, Cracow, Poland) and Stargraphics Centurion 18 ver.18.1.12 (StarPoint Technologies, Inc., VA, USA) were used to perform all statistical tests. A statistical significance level of 0.05 was assumed. The Shapiro–Wilk test was used to confirm the normality of distribution. As the distribution of samples was normal, parametric statistical tests were performed. The analysis of variance (ANOVA) and the post-hoc least significant difference test were applied to reveal fractal dimension and textural feature differences between the examined microstructures of all materials, the same fracture zones of all materials and between fracture zones of the same material, differences of flexural strength, flexural moduli and microhardness values. The Pearson correlation coefficient (R) was used to estimate the correlation of FD between σf and Ef. The correlation coefficient was also calculated to identify relations between filler content by volume and σf; filler content by volume and Ef; filler content by volume and HV01.
4
Statistical Analysis of In Vivo Samples
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Statistical analyses were performed with Statistica version 13.3 (StatSoft, Kraków, Poland). In vivo samples were analyzed in duplicate; the values for each group represent the mean of eight animals (n = 8). All results were expressed as means and standard deviation, and all variables were normalized using the Shapiro–Wilk test. The data obtained were subjected to analysis of variance (ANOVA) using a linear model procedure. The significance of the differences between the test results was determined by the NIR test. The significance level was established for p < 0.05 to evaluate the differences between the studied groups.
5
Body Composition of Polish Adolescents
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The sample size was calculated for the population of Polish female adolescents aged 15–20 years, at a 95% confidence level and 5% margin of error while assuming a percentage of 50%. The required sample size was estimated as 384 respondents, so the sample of 818 female adolescents was interpreted as sufficient.
The data distribution was controlled using the Shapiro–Wilk test. The nonparametric Kruskal–Wallis analysis of variance (ANOVA) with post hoc Tukey test was used for comparison of multiple groups.
The statistical analysis was conducted using Statistica version 13.3 (StatSoft Inc., Tulsa, OK, USA), while p ≤ 0.05 was indicated as a statistically significant difference.
The data distribution was controlled using the Shapiro–Wilk test. The nonparametric Kruskal–Wallis analysis of variance (ANOVA) with post hoc Tukey test was used for comparison of multiple groups.
The statistical analysis was conducted using Statistica version 13.3 (StatSoft Inc., Tulsa, OK, USA), while p ≤ 0.05 was indicated as a statistically significant difference.
6
Statistical Analysis of Experimental Data
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All statistical analyzes were performed with STATISTICA version 13.3 (StatSoft®, Inc. 2017, https: //www.statsoft.com). Categorical variables were expressed as percentages and continuous variables as mean ± SD.
The Shapiro-Wilk test was used to calculate whether a random sample of data comes from a normal distribution. To compare the differences between two independent samples when the sample distributions were not normally distributed, the Mann -Whitney U test or the Kruskal-Wallis ANOVA tests were used. In the case of a normal distribution, the Student's t-test or ANOVA test supplemented with the Newman-Keuls post hoc test was performed. A χ2 test was used for the analysis of qualitative characteristics. Additionally, a correlation analysis was performed using Spearman's rank. A p-value of < 0.05 was accepted as statistically significant.
The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Declaration of Helsinki of 1975, as revised in 2008.
Written consent was obtained from all subjects/patients and full anonymization of the data was guaranteed.
The Shapiro-Wilk test was used to calculate whether a random sample of data comes from a normal distribution. To compare the differences between two independent samples when the sample distributions were not normally distributed, the Mann -Whitney U test or the Kruskal-Wallis ANOVA tests were used. In the case of a normal distribution, the Student's t-test or ANOVA test supplemented with the Newman-Keuls post hoc test was performed. A χ2 test was used for the analysis of qualitative characteristics. Additionally, a correlation analysis was performed using Spearman's rank. A p-value of < 0.05 was accepted as statistically significant.
The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Declaration of Helsinki of 1975, as revised in 2008.
Written consent was obtained from all subjects/patients and full anonymization of the data was guaranteed.
7
Assessing Sperm DNA Damage Risk
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Statistical analysis was carried out using the software Statistica version 13.3 (StatSoft, Poland) and MedCalc version 15.2.2 (MedCalc Software, Belgium). Two independent group comparisons were performed using the Mann–Whitney U test for continuous variables. A chi-square test was used to compare the categorical data. The quantitative variables are expressed as the median (range) and means ± standard deviations (SDs), while qualitative data are presented as percentages. To define a risk for having high sperm DNA damage, an OR was calculated and is presented with the 95% confidence interval (CI) and p value. For all statistical tests, a p value of 0.05 was deemed significant.
8
Statistical Analysis of Consumer Data
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All the obtained results were subjected to analysis of variance (ANOVA) with Duncan’s post hoc test at 95% confidence level and to linear regression analysis in the Windows software called STATISTICA, version 13.3 (StatSoft Inc., Tulsa, OK, USA).
Values obtained by the consumer test were analyzed by the Kruskal–Wallis test (test H).
Values obtained by the consumer test were analyzed by the Kruskal–Wallis test (test H).
9
Statistical Analysis of Experimental Data
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Data were analyzed in STATISTICA version 13.3 software (https://statistica.software.informer.com/13.3/ (accessed on 25 May 2022); StatSoft, Tulsa, OK, USA). All samples were prepared in triplicate and the experiments were performed twice. The results are presented as the mean ± standard deviation. The normality of the data distribution was verified using the Shapiro–Wilk test. Normal distributed data were analyzed using one-way analysis of variance with Tukey’s post hoc test. For results with a nonnormal distribution, the nonparametric Mann–Whitney U test was performed and the means were compared based on the p values for multiple comparisons.
10
Evaluating Kindergarten Menu Nutrient Profiles
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Two-way variance analysis (ANOVA) was used to evaluate changes in energy value and nutrients in kindergarten menus. The effect of such factors as the kindergarten (A, B, C, D), the season (summer and autumn), and a couple of interactions between them were analyzed. When a significant main effect or interaction was identified, the mean values were further analyzed using the Tukey’s multiple range test. The results were presented as a mean ± standard deviation. The experimental data were analyzed using Statistica version 13.3 (StatSoft Inc., Kraków, Poland) [36 ]. Differences with a probability level <0.05 were considered significant.
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