Tables and figures were processed with Microsoft Excel 2007 and SigmaPlot 14.0 Software. Data management and analysis were performed using Data Processing System software 7.05 (DPS) and IBM SPSS statistics 22 statistical software. The means and significant differences between treatments were separated using the least significant difference (LSD) test at 5% probability.
Excel 2007
Manufactured by Merck Group
Sourced in United States
Excel 2007 is a spreadsheet software program developed by Microsoft. It allows users to organize, analyze, and visualize data in a tabular format. Excel 2007 includes tools for creating charts, performing calculations, and managing large datasets.
Automatically generated - may contain errors
9 protocols using excel 2007
1
Quantitative Analysis of Experimental Treatments
2
Evaluating Inhibitory Potency
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All experiments were carried out in triplicate, and the results are expressed as mean ± standard deviation (SD). The concentrations of the samples that provide 50% inhibition (IC50) were obtained by interpolation from linear regression analysis. The results were tested for normal distribution by Kolmogorov-Smirnov test. Correlations were assessed using Pearson's correlation coefficient (r). One way analysis of variance (ANOVA) coupled with the Holm-Sidak post hoc tests was used to compare the data and to identify means with significant differences. Differences with P < 0.05 were considered statistically significant. The data analysis was performed using Microsoft Excel 2007 software and SigmaPlot for Windows (version 12.0).
3
Neurophysiological Effects of Stress Response
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Figures are shown as mean ± standard error of the mean. Comparisons were made using Two-tailed Student's t-test run on Microsoft Excel 2007 or Two-Way ANOVA run on Sigmaplot 11.0 software. The post-hoc test, Holm-Sidak Method, was used for all pairwise multiple comparison. A p-value ≤ 0.05 indicated significant group difference.
4
Modeling Cotton Nutrient Accumulation
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The cotton N, P, and K contents were not significantly different between the two growing seasons in the field; therefore, the values presented are the means of 2 yr. Microsoft Excel 2007 and SigmaPlot 12.0 were used for data processing and figure drawing, respectively. SPSS 12.0 was used for performing ANOVA and regression analysis. A logistic formula was used to describe the progression of N, P, and K accumulation as follows6 (link): Here, t (d) represents the DAE; Y(g) represents the N, P, and K contents at t; K(g) represents the maximum content; and a and b are constants to be retrieved.
From formula (1):
When t = t0, the N, P, and K accumulation has a VM calculated as follows:
The period during which 58% of the N, P, and K has accumulated is defined as the N, P, and K (FAP), which begins at t1 and ends at t2. During the FAP, Y is linearly correlated with t, and the VT is calculated as follows:
From formula (1):
When t = t0, the N, P, and K accumulation has a VM calculated as follows:
The period during which 58% of the N, P, and K has accumulated is defined as the N, P, and K (FAP), which begins at t1 and ends at t2. During the FAP, Y is linearly correlated with t, and the VT is calculated as follows:
5
GC-MS Data Mining Protocols for Metabolomics
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GC-MS data mining was carried out according to the methods of Aggio et al. [44 (link)] and Pinu et al. [30 (link)] using in-house R-based software and scripts (Version 3.0.1). ANOVA and t-tests were also performed using two different in-house R scripts. For other data analysis, Microsoft® Excel 2007 and SigmaPlot 12.0 were used. Hierarchical Cluster Analysis (HCA) was performed using a web interface, Metaboanalyst 3.0 (http://www.metaboanalyst.ca ), created by the University of Alberta, Canada [45 (link)].
6
Allium cepa Extract Effects Evaluation
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The data was collected in case record forms. Then they were entered into excel spreadsheet 2007. Statistical analysis was performed using Microsoft Excel-2007 and Sigma graph pad prism version-5 USA. Data was described as mean±standard deviation. One way ANOVA followed by post hoc Bonferroni multiple comparison tests was used for analysis of data among all groups. All the results of test drug (Allium cepa) were compared with control. For all inferential statistical tests, a two tailed p value of less than 0.05 was considered significant.
7
Photosynthetic Parameters Correlation
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Pearson correlation was used to calculate the correlation coefficients between photosynthetic parameters, and a bilateral method was used to test the correlation between photosynthetic parameters. Pearson correlation was used to calculate the correlation coefficients among Pn, δ software was used for statistical analysis, Microsoft Excel 2007 was used for data collation and calculation, and Sigmaplot 10.0 software was used for drawing.
8
Cod Stomach Contents and Parasite Infection
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Stomach content of cod was expressed as the percentage of all stomachs in a certain size class (frequency of occurrence) carrying a certain prey organism. The infection percentages of cod and the mean number of worms per infected fish in the different size classes were calculated. Differences were evaluated by the Mann-Whitney U-test. Microsoft Excel 2007 and SigmaPlot 12.5 were used for statistical calculations. A probability level of 5% was used for all analyses.
9
Phylogenetic Analysis of Parasite Prevalence
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Prevalence (percentage of the cod population infected), mean intensity (mean number of worms per infected fish) were calculated according to Bush et al. (1997) . Differences between mean intensities in different size groups were evaluated by the Mann-Whitney U-test. Microsoft Excel 2007 and SigmaPlot 12.5 were used for statistical calculations and a probability level of 5% was used for all analyses.
Phylogenetic analysis. In general the resources of the software package CLC Main Workbench v 7.7.2 were used. The sequences excluding the primer binding sites were aligned using Clustal W. In order to trim the alignment the web-based software Gblocks (Castresana Lab) was used but no matter which stringency levels that were used no blocks to be omit was identified. Four different methods (hierarchical Likelihood Ratio Tests (hLRT), Bayesian Information Criterion (BIC), Akaike Information Criterion (AIC) and Akaike corrected Information Criterion (AICc)) were used to test for the best model for the construction of phylogenetic trees. The tested models were Jukes-Cantor (JC), Felsenstein 81 (F81), Kimura 80 (K80), Hasegawa-Kis hino-Yano (HKY) and General Time Reversible (GTR). The phylogenetic tree was achieved by using the model GTR+G+T as all four methods recommended it as the best choice. Bootstrap analysis was performed with 1,000 replicates.
Phylogenetic analysis. In general the resources of the software package CLC Main Workbench v 7.7.2 were used. The sequences excluding the primer binding sites were aligned using Clustal W. In order to trim the alignment the web-based software Gblocks (Castresana Lab) was used but no matter which stringency levels that were used no blocks to be omit was identified. Four different methods (hierarchical Likelihood Ratio Tests (hLRT), Bayesian Information Criterion (BIC), Akaike Information Criterion (AIC) and Akaike corrected Information Criterion (AICc)) were used to test for the best model for the construction of phylogenetic trees. The tested models were Jukes-Cantor (JC), Felsenstein 81 (F81), Kimura 80 (K80), Hasegawa-Kis hino-Yano (HKY) and General Time Reversible (GTR). The phylogenetic tree was achieved by using the model GTR+G+T as all four methods recommended it as the best choice. Bootstrap analysis was performed with 1,000 replicates.
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