Spss statistic v 23

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SPSS Statistics V.23 is a software package used for statistical analysis. It provides a range of statistical and analytical tools for data management, data analysis, and reporting. The core function of SPSS Statistics V.23 is to enable users to perform various statistical procedures and analyses on data.

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SPSS Statistics (9452 citations) SPSS 23.0 (3579 citations) SPSS Statistics 23 (2711 citations) SPSS Statistic 23 (48 citations) Statistics 23.0 (34 citations) SPSSTM (8 citations) SPSS PASW Statistic v.23.0 (3 citations) SPSS vs. (2 citations) SPSS Statistic software (v.23) (2 citations)

8 protocols using spss statistic v 23

Determination of Glucosinolate and Isothiocyanate Recovery

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To further
evaluate the applicability of the
method for analyzing extracts, recovery was determined by analyzing
the three different Brassicaceae seed extracts (i.e. S. alba, B. napus,
and B. juncea), spiked with 14 GSL
and 15 ITC standards (each at two levels: 10 and 30 μM), derivatized
with NAC. Recovery (%) was calculated as where x_spiked was
the measured concentration of the analyte in the spiked experiment, x_unspiked was the measured concentration of the
analyte in the unspiked experiment, and x_ref was the true concentration which was spiked to the extract. Four
repetitions were performed.
According to FDA,⁴⁰ a good recovery for the working analyte concentrations
in this study should be between 80 and 110%. To test whether the recovery
was within the range, the recovery whose average outside the range
was statistically evaluated by analysis of variance (ANOVA) one-sample t-test using IBM SPSS Statistic v.23 software (SPSS Inc.,
Chicago, IL, U.S.A.).

Andini S., Araya-Cloutier C., Sanders M, & Vincken J.P. (2020). Simultaneous Analysis of Glucosinolates and Isothiocyanates by Reversed-Phase Ultra-High-Performance Liquid Chromatography–Electron Spray Ionization–Tandem Mass Spectrometry. Journal of Agricultural and Food Chemistry, 68(10), 3121-3131.

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Statistical Analysis of Gene Expression

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Normality was assessed with a Kolmogorov–Smirnov. Normally distributed continuous variables were provided as mean ± standard deviation and non-normally distributed continuous variables as median (interquartile). A chi-square test was used for reporting associations between two categorical variables. Differences of continuous variables between groups were analyzed by the Mann–Whitney test. The correlation between gene expression levels was represented by the Pearson correlation coefficient. Models were otherwise validated by examining standardized residuals for normal distribution. Statistical analysis was performed using IBM SPSS statistic V.23 (Armonk, New York, USA). A P value of less than 0.05 was considered significant.

Tian Y., Li J., Tian X, & Zeng X. (2021). Using the co-expression network of T cell-activation-related genes to assess the disease activity in Takayasu’s arteritis patients. Arthritis Research & Therapy, 23, 303.

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Statistical Analysis of Gene Expression

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Normality was assessed with a Kolmogorov–Smirnov. Normally distributed continuous variables were provided as mean ± standard deviation and non-normally distributed continuous variables as median (interquartile). A Chi-square test was used for reporting associations between two categorical variables. Differences of continuous variables between groups were analyzed by the Mann–Whitney test. The correlation between gene expression levels was represented by the Pearson correlation coefficient. The models were otherwise validated by examining standardized residuals for normal distribution. Statistical analysis was performed using IBM SPSS statistic V.23 (Armonk, New York, USA). A p-value of less than 0.05 was considered significant.

Tian Y., Huang B., Li J., Tian X, & Zeng X. (2022). Identification of the Association Between Toll-Like Receptors and T-Cell Activation in Takayasu’s Arteritis. Frontiers in Immunology, 12, 792901.

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Gene Co-Expression Network Analysis

Cited 2 times

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We constructed the gene co-expression network of the healthy control group, the untreated TAK group, the treated TAK group, the inactive-treated TAK group, and the active-treated TAK group based on the qPCR dataset, respectively. The Pearson correlation has an advantage in predicting the interaction of molecules and is widely used as a measure of gene co-expression in many public databases (37 (link), 38 (link)), so it was adopted the main approach in the network analysis and the results were available in the main text. However, Spearman correlation has an advantage in revealing the functional associations, so it was adopted as a complementary approach and the results are available in the Supplementary Information (39 (link)). Statistical analysis was performed using IBM SPSS statistic V.23 (Armonk, New York, USA). A p-value of less than 0.05 was considered significant. Cytoscape V. 3.8.2 was used to edit the networks.

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Statistically Evaluating Treatment Effects

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To test for significance between
treatments within species, the data were statistically evaluated by
analysis of variance (ANOVA), followed by Tukey post hoc analysis
using IBM SPSS Statistic v.23 software (SPSS, Inc., Chicago, IL, U.S.A.).

Andini S., Dekker P., Gruppen H., Araya-Cloutier C, & Vincken J.P. (2019). Modulation of Glucosinolate Composition in Brassicaceae Seeds by Germination and Fungal Elicitation. Journal of Agricultural and Food Chemistry, 67(46), 12770-12779.

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ARPE-19 Cell Proliferation Analysis

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All data were collected in a database created in Excel (Microsoft Office Excel 2016; Microsoft Corporation, Redmond, WA, USA) and subsequently analyzed by SPSS software (IBM SPSS statistic v23, SPSS Inc. Chicago, IL, USA). Values were expressed as mean ± standard error of the mean (SEM), and differences were considered statistically significant at p < 0.05 in all cases. Before statistical analysis, fluorescence data were normalized by log-transforming using the logarithm base two to obtain a normal distribution. Analysis of ARPE-19 cell proliferation at follow-up times was performed by repeated-measures analysis of variance (ANOVA) with Bonferroni corrections for multiple testing and Tukey's post hoc tests since the homogeneity of variance was validated (Levene's test). A comparison of means in other experiments with a normal distribution, where the homogeneity of variance was not validated (Levene's test), was performed by Welch test with Games-Howell post hoc test. Finally, in the case of nonparametric variables, group means were compared using the Kruskal-Wallis test. Graphs were made using Excel.

Alonso-Alonso M.L., Srivastava G.K., Usategui-Martín R., García-Gutierrez M.T., Pastor J.C, & Fernandez-Bueno I. (2020). Mesenchymal Stem Cell Secretome Enhancement by Nicotinamide and Vasoactive Intestinal Peptide: A New Therapeutic Approach for Retinal Degenerative Diseases. Stem Cells International, 2020, 9463548.

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Comparison of Dietary Treatments

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All data were presented as the means±standard deviations. Data were analyzed for difference among the groups by Duncan’s multiple range tests following the one-way analysis of variance using SPSS (SPSS Statistic v.23.0, IBM Corp.). Differences were considered statistically significant at P<0.05.

Cho W., Park J., Lee M., Park S.H., Jung J., Kim J., Eun S, & Kim J. (2023). Gly-Pro-Val-Gly-Pro-Ser Peptide Fish Collagen Improves Skin Moisture and Wrinkles with Ameliorated the Oxidative Stress and Pro-inflammatory Factors in Skin Photoaging Mimic Models. Preventive Nutrition and Food Science, 28(1), 50-60.

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Statistical Analysis of Experimental Data

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Means of groups were compared by ANOVA Tukey's multiple comparison test, performed using SPSS statistic v. 23.0 (IBM). Jitterplot drawing and correlation analysis was performed using RStudio v. 3.6.3 (https://www.rstudio.com/).

Tiwari R., Kaur J, & Bisht N.C. (2021). Extra‐large G‐proteins influence plant response to Sclerotinia sclerotiorum by regulating glucosinolate metabolism in Brassica juncea. Molecular Plant Pathology, 22(10), 1180-1194.

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