Descriptive statistical parameters for DB and WUE were calculated on wheat phenotyping data, ANOVA analysis was performed with SigmaPlot ver.13 (Systat Software Inc.). The F test statistic, calculated as the ratio between estimated population variance between groups and estimated population variance within groups, was determined. To demonstrate the correlation between DB and fresh weight biomass harvested a Linear Correlation Analysis was performed (SigmaPlot ver.13, Systat Software Inc.). Phenotyping data from the tomato trial were analyzed using one-way analysis of variance (ANOVA), and the means were compared using the Duncan’s New Multiple Range Test (MRT; p < 0.05) employing the R package agricolae (Mendiburu, 2016 ).
Sigma plot ver 13
Manufactured by Grafiti LLC
Sourced in United States
Sigma Plot ver. 13.0 is a data analysis and graphing software. It provides tools for data visualization, statistical analysis, and curve fitting.
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Lab products found in correlation
6 protocols using sigma plot ver 13
1
Wheat and Tomato Phenotyping Analysis
2
Evaluation of Surface Roughness and Hardness
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The sample size was determined based on the effect size f = 1.00, α = 0.05, β = 0.2, power = 0.80, and the number of groups. A power analysis suggested that nine samples would be adequate for effective measurements of Ra and KHN. Therefore, the present study was initially conducted using sample sizes of 10 for Ra and KHN measurements. After data collection, post-hoc power tests were performed using a statistical software system (Sigma Plot ver. 13.0; Systat Software, Chicago, IL, USA), which indi- After the confirmation of normal distribution (using the Kolmogorov-Smirnov test) and homogeneity of variance (using Bartlett's test), the Ra data for each group were subjected to analysis of variance (ANOVA) followed by Tukey's HSD test at a significance level of 0.05. The analysis factors involved 1) whether PMTC was conducted or not, 2) the type of the PMTC paste, and 3) the type of the material. One-way ANOVA followed by Tukey's HSD test (α = 0.05) was used for comparisons within subsets of the Ra and KHN data. The statistical analyses were conducted using statistical software (Sigma Plot ver. 13.0).
3
Evaluating Experimental Mouse Metadata
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All data was log transformed and checked for normality by the Shapiro–Wilk test and for equal variance by the Brown-Forsythe test. MRI and MFAA data were not log transformed to obtain a normal distribution. Except for gut microbiome, data was analyzed using two-way ANOVA without repeated measurements. Whenever significant effects of time, group/mice or interaction were seen, Student–Newman–Keuls post-hoc test was applied (SigmaPlot, ver. 13.0, Systat Software Inc, CA, USA). For gut microbiota analysis the influence of mice strain and time on alpha-diversity was assessed with two-tailed student’s t-test, while beta-diversity was analyzed using Adonis test based on Sørensen-Dice dissimilarities as implemented in the Vegan R-package56 . Differences in the ratio of species frequencies between experimental groups (up to 362 evaluated species for each group) were analyzed using G-test (Goodness of fit) and adjusting all P-values for multiple testing with Bonferroni correction.
P-values below 0.05 were considered significant and trends are reported for p-values between 0.05 and 0.10. Data are shown as geometric mean ± back-transformed standard error of mean (SEM) unless otherwise specified.
P-values below 0.05 were considered significant and trends are reported for p-values between 0.05 and 0.10. Data are shown as geometric mean ± back-transformed standard error of mean (SEM) unless otherwise specified.
4
14-Day Cycling Effects on Metrics
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The statistics were calculated using Sigma Plot ver. 13.0 (Systat Software Inc., San Jose, USA). To assess changes before and after the 14 days of cycling a two-tailed paired t-test was used. Results are given as mean ± SEM., if not otherwise stated. In all cases, P < 0.05 was used as the level of significance in a two-tailed test.
5
Comparative Analysis of Treatment Outcomes
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All results are presented as the mean±standard deviation. The statistical analysis was performed using SPSS ver. 14.0 (SPSS Inc., Chicago, IL, USA) and SigmaPlot ver. 13.0 (Systat Software, Palo Alto, CA, USA). Analysis of variance was employed to compare the groups. All p-values less than 0.05 were considered statistically significant.
6
Analyzing Herbicide Response in Crop Populations
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Shoot fresh weight data were analyzed using ANOVA in JMP (ver. 15) statistical package (SAS Institute Inc., Cary, NC, USA). Data was visualized using SigmaPlot (ver. 13) software (Systat Software Inc., San Jose, CA, USA). The assumptions of homoscedasticity and normality were met using Levene′s tests. For both experiments, i.e., the response of GO and GY populations to herbicide treatments at different growth stages and the synergistic effect of surfactant application, interactions between experimental parameters were observed. Thus, data from each experiment were analyzed separately as experiment-by-treatment. For all experiments, shoot fresh weight was analyzed as percent of untreated control. All parameters were subjected to one-way ANOVA and means were separated using the Tukey-HSD test (α = 0.05).
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