The Kolmogorov–Smirnov test is used to judge whether the measurement data conform to the normal distribution. The t-test is used for continuous measurement data and meeting normal distribution. The Mann–Whitney U rank sum test was used for comparison between measurement data groups that did not conform to normal distribution. Pearson is used for classified data χ2 inspection. The data were statistically analyzed by SPSS20.0 analysis software. P < 0.05 was statistically significant.
Spss 20.0 analysis software
Manufactured by IBM
Sourced in United States
SPSS 20.0 is an advanced statistical analysis software developed by IBM. It provides a comprehensive set of tools for data management, analysis, and reporting. The core function of SPSS 20.0 is to enable users to perform a wide range of statistical procedures, including descriptive statistics, hypothesis testing, regression analysis, and more. The software offers a user-friendly interface and supports a variety of data formats.
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Lab products found in correlation
10 protocols using spss 20.0 analysis software
1
Statistical Analysis of Measurement Data
2
Multiomic Approach for Microbiome Analysis
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All statistical analyses were conducted using SPSS 20.0 analysis software (SPSS Inc., Chicago, IL, USA). Data were analyzed by one-way ANOVA followed by the Tukey’s post hoc test. Bioinformatics analysis of RNA-seq and 16S rRNA sequence, including species abundance, was performed using Omicsmart (Genedenovo Biotechnology Co. Ltd., Guangzhou, China), microbiota data were analyzed by Kruskal–Wallis one-way ANOVA followed by Wilcoxon–Mann–Whitney test (data not normally distributed). Significance was set at p < 0.05 for all tests, data were expressed as Mean ± SEM.
3
AI-Assisted Metastatic Lymph Node Diagnosis
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Statistical analysis of the data was performed using the SPSS 20.0 analysis software (SPSS Inc., Chicago, IL, USA). Comparisons among count data were performed using the Chi-square test. P < 0.05 was considered statistically significant. The sensitivity, specificity (FP rate) and accuracy of the artificial intelligence diagnosis system for metastatic lymph nodes were also analyzed, and the receiver operating characteristic (ROC) and precision-recall (PR) curves were generated. The ROC curve was mainly used as the basis of the analysis, and the area under the ROC curve (AUC) of the FR-CNN-based artificial intelligence-assisted diagnosis was calculated using the trapezoidal method.
4
Statistical Analysis of Group 6 LN Metastasis
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Statistical data analyses were performed using SPSS 20.0 analysis software (SPSS, Chicago, IL). t-Tests were used to compare measurement data, and chi-square tests were used to compare count data. A Fisher's exact test was used for statistical comparison, and this test was chosen because the complication rates do not follow a normal distribution, are relatively rare, and are divided between two categorical variables. Multiple logistic regression analysis was performed to determine which variables affected group 6 LN metastasis. Statistical significance was defined as P < 0.05.
5
Quantitative Analysis of Protein Interactions
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Graphs were drawn using Excel 2019 (Microsoft, Redmond, WA, USA). Data were expressed as mean ± standard error, calculated by SPSS 20.0 analysis software (IBM, Chicago, IL, USA), and assessed using analysis of variance to determine statistical significance. Student’s t-test (* p < 0.05; ** p < 0.01; *** p < 0.001) was used to estimate significant effects. Photographs were edited in Microsoft PowerPoint 2019.
6
Infection Rates in Guillain-Barré Syndrome
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Normally distributed continuous data were presented as means and standard deviations. The categorical variables were shown as n (%). The difference in the frequency of infections in patients with GBS and the controls was compared by the Chi‐square test or Fisher's exact test. For patients with and without infections, the difference in demographic and clinical features, anti‐glycolipid antibodies, and clinical subtypes were compared by Chi‐square test or Fisher's exact test. The analysis was performed with the SPSS 20.0 analysis software (IBM, Armonk, NY). A two‐sided P < 0.05 was considered to be significant.
7
Comparative Analysis of Experimental Treatments
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The data were evaluated using analysis of variance to determine statistical significance and were represented as means ± SD, as calculated by SPSS20.0 analysis software (IBM, Chicago, IL, USA). A difference was considered significant at the 95% confidence level (p < 0.05). All photographs were taken with a Nikon D5300 camera (Nikon Corporation, Tokyo, Japan) and edited in ImageJ. Graphs were plotted using Excel 2019 (Microsoft, Redmond, WA, USA) and figures were assembled using Microsoft PowerPoint.
8
Intestinal Microbiota Diversity Analysis
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All trial data were expressed as mean ± SD (standard deviation, n = 4) and analyzed by one-way ANOVA model using SPSS 20.0 analysis software (IBM, Armonk, NY, USA). Duncan’s test was used for multiple comparisons if significant differences existed. p < 0.05 indicated a statistically significant difference. When data were expressed as percentages, squared arcsine transformation was performed before statistical analysis. For intestinal microbiota analysis, the alpha diversity index was analyzed using QIIME (v1.8.0, http://bio.cug.edu.cn/qiime/ accessed on 24 October 2021) software and Lefse analysis was performed using R-Statistical software v3.6.0 (R Statistical Corp., Vienna, Austria). The Linear Discriminant Analysis (LDA) score screening value was set to 3, p < 0.05.
9
Comparison of Visual and Cognitive Metrics
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The visual acuity, average response time, and head velocity while turning were exported and processed in LabVIEW2013 (National Instruments, USA). With unequal sample sizes between the two groups, independent t-test compared the difference between the healthy participants and patients. The level of significance was set at α<0.05. Statistical analyses were performed using the SPSS 20.0 analysis software (Armonk, NY: IBM Corp.).
10
Statistical Analysis of Experimental Data
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Representative results from three independent experiments were shown and were presented as mean ± standard error. Differences between groups were evaluated by one-way analysis of variance. A level of p<0.05 was considered significant. Analysis was performed with the SPSS 20.0 analysis software by IBM (Armonk, NY, USA).
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