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Spss statistics 26.0 program

Manufactured by IBM
Sourced in Germany, United States

SPSS Statistics 26.0 is a software program for statistical analysis. It provides tools for data management, analysis, and presentation. The program is designed to handle a wide range of data types and can be used for various statistical techniques, including regression analysis, hypothesis testing, and data mining.

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Lab products found in correlation

3 protocols using spss statistics 26.0 program

1

Statistical Analysis of Biological Data

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Data are shown as boxplots or bar charts (± standard deviation), and Mann Whitney U-test, Kruskal–Wallis Test and Spearman correlation were used as statistical tests (SPSS Statistics 26.0 program, IBM, Leibniz Rechenzentrum, München. Germany). Continuous variables in the tables and the text of the manuscript are given as median and interquartile range. The Chi-square test was performed for categorical variables and an unpaired t-test for paired data (Ms Excel 2016). A value of P < 0.05 was regarded as significant.
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2

Exploring Biomarker Correlations in Disease

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Data are shown as boxplots and outliers are marked as circles and asterisks. A receiver operating characteristic curve, Mann–Whitney U-test, Kruskal–Wallis Test, and Spearman correlation were the statistical tests used (SPSS Statistics 26.0 program, IBM, Leibniz Rechenzentrum, München, Germany). A value of p < 0.05 was regarded as significant.
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3

Ceramide Profiling in Disease Samples

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Data are shown as boxplots, which gives the minimum, the maximum, the median, and the first and third quartiles. Small circles or asterisks above or below the boxes mark outliers. When more than one ceramide species was displayed in a figure, data are shown as mean concentration ± 95% confidence interval.
Data are reported as median values, and the minimum and maximum values are given in brackets.
The non-parametric Kruskal–Wallis test was used for comparison of continuous variables between independent groups. Student’s t-test was used to analyze paired data, and Spearman’s correlation was used for correlation analysis (SPSS Statistics 26.0 program, IBM, Armonk, NY, USA). Chi-squared test (MS Excel, Microsoft Co., Ltd., Albuquerque, NM, USA) was used for categorical variables. Data were corrected for multiple comparisons. A value of p < 0.05 was regarded as significant.
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