In this experiment, independent samples Tukey test was performed using SPSS 25.0 statistical software. p < 0.05 indicated that the difference was statistically significant. Other data were processed using mean ± standard deviation, and OriginPro 2012 was used for plotting. KneadData software was used for quality control (based on Trimmomatic) and host removal (based on Bowtie2) of the raw data. Before and after KneadData, FastQC was used to check the rationality and effect of quality control [32 (link),33 (link)]. Starting from the quality-controlled reads and the reads with host genes removed, HUMAnN3 software (based on DIAMOND) was used to align the reads of each sample to the database (UniRef90). According to the UniRef90 ID and the corresponding relationship of each database, the annotation information and relative abundance table of each functional database were obtained [34 (link),35 (link),36 (link),37 (link)]. The original data obtained from liquid chromatography-mass spectrometry (LC-MS/MS) was processed using Proteowizard software (v3.0.8789).
Spss 25.0 statistical
Manufactured by IBM
Sourced in United States
SPSS 25.0 is a statistical software package designed for data analysis and management. It provides a range of tools for descriptive statistics, advanced statistical modeling, and data visualization. The software is widely used in various fields, including social sciences, market research, and scientific research.
Automatically generated - may contain errors
Lab products found in correlation
Prism 8, by GraphPad (6 mentions)
Sigmaplot 10, by Grafiti LLC (1 mentions)
Simca p, by Sartorius (1 mentions)
Epidata version 3, by IBM (1 mentions)
Prism 7, by GraphPad (1 mentions)
Sample size calculator, by Raosoft (1 mentions)
Prism 8, by IBM (1 mentions)
Prism 9, by GraphPad (1 mentions)
Jmp 13, by SAS Institute (1 mentions)
141 protocols using spss 25.0 statistical
1
Microbial Functional Profiling from Sequencing
2
Statistical Analysis of Experimental Data
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The data were calculated by SPSS 25.0 statistical software and presented as mean ± standard deviation. Difference of measurement data was compared and analyzed by the intergroup independent sample t-test or repeated measure ANOVA, and the counting data were analyzed through Fisher's exact probability test or χ2. P < 0.05was statistically significant.
3
Statistical Analysis of Clinical Data
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Clinical data were statistically analyzed using SPSS 25.0 statistical software. Measurement data that conforms to a normal distribution were presented as x ± s, and the independent samples t-test was used to compare the differences between groups. Categorical data were tested using the χ2 test or Fisher’s exact test, and differences were considered statistically significant at P < 0.05. For the machine learning results, ROC curves were used in the training cohort and testing cohort to compare model prediction accuracy and calculate AUC, sensitivity, and specificity. The Delong test was used to compare the AUC differences between the ROC curves of the two models, and P < 0.05 was considered statistically significant.
4
Statistical Analysis of Experimental Data
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Statistical analysis was performed on experimental data using SPSS 25.0 statistical software. The measurement data are expressed as the mean ± SD. The independent-sample t test was used for comparisons between 2 groups. Analysis of variance (ANOVA) was used for comparisons between 3 or more groups. Fisher’s least significant difference (LSD) test and the Student–Newman–Keuls multiple range (SNK) test were used for pairwise comparison within groups. A difference was considered statistically significant at P < 0.05.
5
Statistical Analysis of Intracranial Infection in Brain Tumor Surgery
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SPSS 25.0 statistical software is used for data analysis, and the specific steps include the following: (1) measurement data: the normality test is performed on the data first. If the data followed normal distribution and homogeneity of variance, it is represented by mean ± standard deviation. The paired sample t test is used for test within the group. (2) Count data: descriptive statistical analysis is conducted by percentage, and x2 test is performed. (3) Multivariate analysis: logistic regression is used to analyze the risk factors of intracranial infection after brain tumor surgery. The abovementioned data show a significant difference with P < 0.05. The flow chart of the detailed management scheme is shown in Figure 1 .
6
Predicting HBsAg Loss in Interferon Treatment
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All data were analyzed by SPSS 25.0 statistical software. Normal distribution data were expressed as mean ± standard deviation and independent sample t-test was used for comparison between two groups. Non-normal distribution data were expressed as median and quartile, while Mann-Whitney U nonparametric test was used. The counting data were expressed in frequency and percentage, and chi square test was used. All tests were bilateral tests with P < 0.05 as statistically significant. Bonferroni correction method was used to correct the test standard α when comparing the virological indexes, biochemical indexes and cytokines at 12 and 24 weeks, and the difference was statistically significant if P < 0.025.
We analyzed the relationship between the early (12 and 24 weeks of PEG-IFN α-2a treatment) response of virology, serology, and immunology indexes and HBsAg loss at 48 weeks of interferon treatment.
We analyzed the relationship between the early (12 and 24 weeks of PEG-IFN α-2a treatment) response of virology, serology, and immunology indexes and HBsAg loss at 48 weeks of interferon treatment.
7
Statistical Analysis of Experimental Data
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All data were processed using SPSS 25.0 statistical software. Enumeration data were expressed as N (%). If normally distributed, measurement data were represented as mean ± standard error and median (quartile) if not. Enumeration data were analyzed by χ2 test. The Fisher test analyzed measurement data conforming to a normal distribution, and measurement data not conforming to normal distribution were analyzed by the Kruskal–Wallis test. P < 0.05 was considered statistically significant.
8
Renal Functional Parameters: Age and Gender Differences
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The data were analyzed by SPSS 25.0 statistical software. The intra-class correlation coefficient (ICC) was used to analyze the interrater consistency. An ICC greater than or equal to 0.75 was considered to represent good consistency, an ICC between 0.40–0.75 indicated medium consistency, and an ICC less than 0.40 was considered to represent poor consistency. The measurement data are presented as means ± standard deviations (SD). The paired samples t-test was used to compare the functional parameters between the cortex and medulla of normal kidneys in the same age group. A one-way ANOVA and independent-samples t-test were used to compare the functional parameters of the normal renal cortex and medulla between different age groups and genders. A Pearson linear correlation analysis was used to investigate the association between the functional parameters and the subjects’ age. A P value <0.05 indicated that the difference was statistically significant.
9
Statistical Analysis of Experimental Data
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Data for graphing was processed with GraphPad Prism 9.0 software (GraphPad Software Inc., US). Statistical analysis was performed using the SPSS 25.0 statistical software package. The data were expressed as the mean ± SD. The Student’s t-test was used to compare the two groups of data in the case of a normal distribution and homogeneous variance, and the one-way ANOVA was used to compare more than two groups of data. Nonparametric tests must be used if the data differs from the normal distribution. If p values are lower than 0.05, differences between groups are regarded as statistically significant.
10
Multivariate Analysis of Experimental Data
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The data in all of the tables and figures represented the average values of triplicate experiments. The SPSS 25.0 Statistical Software Program performed ANOVA, Tukey’s test (P < 0.05), and Pearson correlation analysis. The principal component analysis was performed using Canoco 5. The figures were displayed by SigmaPlot 10.0 (Systat Software Inc., San Jose, CA, USA).
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