Excel 2021

Manufactured by IBM

Sourced in United States

Excel 2021 is a spreadsheet software application developed by Microsoft. It provides users with tools for organizing, analyzing, and visualizing data. Excel 2021 offers features for creating formulas, generating charts, and managing large datasets.

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Lab products found in correlation

Spss version 26, by IBM (3 mentions) Spss statistics 26, by IBM (2 mentions) Spss statistic, by IBM (1 mentions) Origin 2021, by IBM (1 mentions) Spss statistics 21, by IBM (1 mentions) Origin 2023, by IBM (1 mentions) Spss statistics 27, by IBM (1 mentions) Spss version 11, by IBM (1 mentions) Spss v22, by IBM (1 mentions)

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Office Excel 2021 (2 citations)

23 protocols using excel 2021

Comparative Data Analysis Protocol

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Data analysis were performed using Excel 2021, and SPSS version 26.0 (International Business Machines, NY, United States). Data indicated mean ± SD with three biological replications. Asterisks indicated significant differences between two lines based on student’s t-test (**p < 0.01).

Yan H., Zhang X., Li X., Wang X., Li H., Zhao Q., Yin P., Guo R., Pei X., Hu X., Han R, & Zhao X. (2022). Integrated Transcriptome and Metabolome Analyses Reveal the Anthocyanin Biosynthesis Pathway in AmRosea1 Overexpression 84K Poplar. Frontiers in Bioengineering and Biotechnology, 10, 911701.

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Comparative Radiation Dosage Analysis

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Statistical analysis was conducted with Microsoft Excel 2021 and IBM SPSS. Descriptive assessment of our study cohort was performed. We assessed whether data in each group was approximately following a normal distribution, however, this could not be proven. Categorical variables were compared with the χ²-test. To compare mean intervention times and radiation dosage, the one-sided Mann–Whitney-U-Test was applied. U-, z-, p- and r-values were reported as indicated. In accordance to Cohen 1992, an r-value between 0.1 and 0.3 was classified as a “weak” effect, between 0.3 and 0.5 as an “intermediate” effect and over 0.5 as a “strong” effect^{10 (link)}. We set the level of significance at an alpha = 0.05.

Mostafa K., Bueno Neves F., Gärtner F., Peters S., Hensler J., Larsen N., Klintz T., Mahnke J., Jansen O, & Wodarg F. (2023). Contour device implantation versus coil embolization for treatment of narrow neck intracranial aneurysms. Scientific Reports, 13, 4904.

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Statistical Analysis of Sample Data

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Microsoft Excel 2021, version 2108 and IBM SPSS Statistics 25 were used to process the data statistically. Descriptive statistics including mean concentrations and standard deviations were calculated (Table S5). To assess statistically significant differences between samples, an ANOVA followed by Tukey’s HSD test was applied to the dataset (Table S5).

Pavlović R., Brodschneider R., Goessler W., Stanisavljević L., Vujčić Z, & Zarić N.M. (2024). Micronutrient Deficiency May Be Associated with the Onset of Chalkbrood Disease in Honey Bees. Insects, 15(4), 269.

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Phenolic Content Bioactivity Correlation

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All the experiments were carried out in triplicate. The standard deviation was calculated and presented together with the mean values. Pearson correlation analysis between total phenolic content and bioactivities was carried out at a 95% confidence level. IBM SPSS Statistics 26 (USA) and Excel 2021 (USA) software packages were used for statistical analysis. Differences were considered to be significant at p < 0.05.

Ispiryan A., Atkociuniene V., Makstutiene N., Sarkinas A., Salaseviciene A., Urbonaviciene D., Viskelis J., Pakeltiene R, & Raudone L. (2024). Correlation between Antimicrobial Activity Values and Total Phenolic Content/Antioxidant Activity in Rubus idaeus L.. Plants, 13(4), 504.

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Evaluating Plant Responses to Salt Stress

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Data processing was conducted using Excel 2021 and IBM SPSS Statistics 26 software, while Origin 2021 and R4.3.1 was utilized for chart creation. A one-way analysis of variance (ANOVA) was employed to analyze the data of various indicators under different salt stress treatments, providing a robust statistical framework for evaluating the effects of salinity on plant physiology.

Mo Q., Liu Y., Wei H., Jiang L., Wu E., Lin L., Yang Q., Yu X., Yan L, & Li Y. (2024). Salt Tolerance in Machilus faberi: Elucidating Growth and Physiological Adaptations to Saline Environments. Biology, 13(2), 75.

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Physiological Responses to Supplementary Light

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The data were analyzed by using Excel 2021 and SPSS version 26.0 (International Business Machines, Armonk, NY, USA). Firstly, to test the effect of all physiological indices, one-way ANOVA was used. The linear model for the analysis of the three treatments was as follows [64 (link)]. Then, multiple comparisons of means were conducted by S-N-K tests at p < 0.05 to assess the physiological responses of different supplementary light sources.

X_{i j} = μ + T_{i} + e_{i j}

where

X_{i j}

is the performance of an individual tree j in treatment i, μ is the overall mean,

T_{i}

is the fixed effect of treatment, and

e_{i j}

is the random error.

Li Y., Zhang X., Zhu Y., Cai K., Li H., Zhao Q., Zhang Q., Jiang L., Li Y., Jiang T, & Zhao X. (2022). Physiological and Transcriptomic Analysis Revealed the Molecular Mechanism of Pinus koraiensis Responses to Light. International Journal of Molecular Sciences, 23(21), 13608.

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Comprehensive Statistical Analysis of Experimental Data

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Statistical analysis was conducted using IBM SPSS Statistics 21.0 and Excel 2021. The normality distribution of the experimental results was tested by the Kolmogorov–Smirnov test, followed by ANOVA with Dunnett's post hoc test for differences between groups. If the data did not fit normal distribution, the Whitney U test was used. All statistical tests were conducted at a 95% confidence level.

Zheng C., Shaposhnikov S., Collins A., Brunborg G., Oancea F., Van Schooten F.J, & Godschalk R. (2023). Comparison of comet-based approaches to assess base excision repair. Archives of Toxicology, 97(8), 2273-2281.

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Image and Data Analysis Workflow

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The data were processed using a suite of software tools including Photoshop CS 5, Origin 2023, IBM SPSS Statistics 27, and Excel 2021.

Li F., Liu G., Zhao L., Gao X., Shen Z., Cao F, & Guo Q. (2023). Morphological Characteristics, Ultrastructure, and Chemical Constituents of the Endotesta in Ginkgo (Ginkgo biloba L.). Plants, 12(20), 3560.

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Honey Bee Gender Differences Analysis

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For statistical analysis, Microsoft Excel 2021, IBM SPSS Statistics 27, and PAST 4.03 were used. To assess statistically significant differences between female (worker) and male (drones) honey bees, we used perMANOVA (PAST 4.03) and MANOVA (SPSS 27). To determine statistically significant differences between individual elements, both parametric MANOVA (tests of between-subjects effects) and Kruskal-Wallis H test were applied to the dataset (SPSS 27). In MANOVA, Wilk's Λ is a measure of the percent variance in dependent variables not explained by differences in levels of the independent variable, and partial η 2 gives information on how large of an effect the independent variables had on the dependent variable. For NDMS ordinary plot, Bray-Curtis distance was used (PAST 4.03).

Zarić N.M., Brodschneider R, & Goessler W. (2024). Sex-specific element accumulation in honey bees (Apis mellifera). Environmental science and pollution research international.

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Effect of Shading on Physiological Parameters

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The subsequent statistical analyses were performed using Excel 2021 and SPSS version 26.0 (International Business Machines, Armonk, NY, USA). One-way ANOVA was performed to test the effect of shading degree on physiological parameters, followed by multiple comparisons of means, which were conducted using S-N-K tests at p < 0.05 to evaluate the different physiological responses of different shading treatments.

Li Y., Zhang X., Cai K., Zhang Q., Jiang L., Li H., Lv Y., Qu G, & Zhao X. (2022). Comparative Transcriptomic and Metabolic Analyses Reveal the Coordinated Mechanisms in Pinus koraiensis under Different Light Stress Conditions. International Journal of Molecular Sciences, 23(17), 9556.

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