The experiments were performed at least on two independent samples; for each sample, the analyses were conducted twice. Significant differences were pointed out through a t-test (paired comparison) or one-way ANOVA (Analysis of Variance) and Tukey’s test (multiple comparison). The p-level was set to 0.05. Statistical analysis was conducted through the software Statistica for Windows, v12.0 (Statsoft, Tulsa, OK, USA).
Statistica for windows v 12
Manufactured by StatSoft
Sourced in United States
Statistica for Windows v. 12.0 is a comprehensive data analysis and visualization software package. It provides a range of statistical tools and functions for data exploration, modeling, and reporting. The software is designed to work on the Windows operating system.
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Lab products found in correlation
7 protocols using statistica for windows v 12
1
Statistical Analysis of Experimental Samples
2
Nitric Oxide Levels Quantification
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The means (± standard deviations, SD) of five replicates are shown. Differences between the means were analyzed for significance using one-way analysis of variance, ANOVA (Statistica for Windows v. 12.0, Stat-Soft Inc., Tulsa, OK, USA). Duncan’s multiple range test was used to test for significance of differences (P ≤ 0.05) between relative NO levels. Two or five independent experiments produced similar results.
3
Soil Heavy Metal Concentration Analysis
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The principal component analysis was used to evaluate significant environmental factors associated with the concentrations of heavy metals in the soil at the sampling points. The Shapiro–Wilk test was used to determine distributions of dependent variables. As the distributions had characteristics of a normal distribution, analysis of variance (two-way with repeated measures) and spread analysis was applied, using the Statistica for Windows v. 12.0 (StatSoft 12). The statistical analysis was performed using the CANOCO v.4.5 statistical package (Braak and Smilaner 2012 ). There were 720 soil samples collected. Each soil sample was mineralised twice independently from each other. All samples were collected at the same year. Typical for agronomic science, a multiyear experiment was deliberately omitted. It was due to very low year to year variability of Cd, Pb, Zn or Cu contents in soil. It is a typical procedure in heavy metal monitoring and assessment in soil (Zhang et al. 2012 (link); Wu et al. 2011 (link); Nabulo et al. 2006 (link); Carrero et al. 2013 (link); Jankaitė et al. 2008 (link); Tóth et al. 2016 (link)).
4
Germination, Ethylene, and Enzyme Assays
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All the experiments were carried out in three, five, or ten biological replicates and the results are expressed as mean ± SD. The means were analyzed for significance using one-way or two-way analysis of variance, ANOVA (Statistica for Windows v. 12.0, Stat-Soft Inc., Tulsa, OK, USA). Duncan's multiple range test was used to test for significance of differences (P ≤ 0.05) in germination experiments, ethylene production analyses, and enzymatic activity assays. Similar results were obtained in two or three independent experiments. Statistical analyses of gene expression fold changes were performed using a post hoc Tukey`s (HSD) test with confidence interval 0.05 and confidence level 95%. Differences between the mean values were considered to be significant at P < 0.01 or P < 0.05.
5
Diabetic Neuropathy Morphometric Analysis
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Statistical analysis was performed using Statistica for Windows v.12 program (StatSoft Tulsa OK, USA). A P value of p < 0.05 was set for statistical significance. Demographic data, clinical parameters of the patient population, CSA, and AFR values were described by descriptive statistics. Depending on normality, unpaired t-test or Mann–Whitney U test was used to compare CSA, AFR values between the patient and the control groups. The Shapiro–Wilk W test was used to check normality. Polyneuropathy and sex ratios were analyzed with Chi-Square test. Diabetic subgroups as well as severity categories of polyneuropathy were compared using Kruskal-Wallis test. To examine the association between CSA and age, height, body mass index (BMI), and HbA1c, the Spearman correlation coefficient was calculated.
6
Standardized Stroke Incidence Comparison
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Normality of continuous variables was evaluated by the Shapiro-Wilk test. Due to non-normal distribution, age at the index event was compared between the districts by the Mann-Whitney test. As to incidence and mortality z-scores were calculated to compare proportions between the populations of the two districts. Acute and long-term case fatality were compared between the 2 districts by chi-squared test. When comparing multiple age-groups we did not make corrections for multiple comparisons. Direct standardization was used to calculate age-standardized incidence and mortality, using the 2013 European Standard Population for standardization [18 (link)]. Kaplan-Meier curves were constructed and the log rank test was used to compare the survival distribution between patients of the 2 districts. The association between mean age at the index stroke and average annual income of the 23 districts was evaluated by Spearman correlation. Statistical significance was set at p <0.05. Statistica for Windows v. 12 (StatSoft, Tulsa, OK) was used for data analysis.
7
Cardiac Hypertrophy Gene Expression Analysis
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The obtained results were analyzed using the Statistica for Windows, v. 12 (StatSoft Inc.). The Shapiro-Wilks W test was used to confirm normal distribution. Values are presented as mean ± standard deviation (SD). Student's t-test was used for comparison between groups (LVH and non-LVH). Using the Affymetrix NetAffx database, 56 mRNAs were selected, which corresponded to cardiac hypertrophy-related genes. The obtained fluorescence signals (FS) were normalized by the RMA Express (log 2 FS) using Matlab software. ANOVA with the Tukey post hoc tests were used to analyze changes in MYL9 and IL6ST over time (T rest , T max , T 15 ). According to the standard method for analyzing the microarray data of gene expression, the results were calculated as a ratio of the normalized FS for the LVH and non-LVH, i.e. as mRNA fold change value (FC). 16 Statistical significance was set at p ≤ 0.05. The Figure was performed using Microsoft Office Excel 2007 (Microsoft Co.).
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