Analytical PCRs resolved by agarose gel electrophoresis, Western blots and micrographs produced similar results in three independent replicates. For FI of GFP, each experiment was run with three biological replicates. For ELISA, each experiment was run with two biological replicates. Statistical analysis was performed by one-way ANOVA test with Tukey Pairwise Comparisons using SPSS 22.0 statistical software. For squalene production, each experiment was run with three biological replicates. Statistical analysis was performed by two-tailed t-test using SPSS 22.0 statistical software.
Spss 22.0 statistical
Manufactured by IBM
Sourced in United States
SPSS 22.0 is a software package for statistical analysis. It provides a comprehensive set of tools for data management, analysis, and reporting. The software is designed to handle a wide range of data types and statistical techniques, including descriptive statistics, regression analysis, and advanced modeling.
Automatically generated - may contain errors
Lab products found in correlation
Prism 5, by GraphPad (5 mentions)
Prism 8, by GraphPad (5 mentions)
Spss statistics for windows version 22, by IBM (3 mentions)
Prism 6, by GraphPad (3 mentions)
Prism 9, by GraphPad (3 mentions)
Prism 7, by GraphPad (3 mentions)
Sas 9, by SAS Institute (2 mentions)
Software, by MedCalc (2 mentions)
Excel 2019, by IBM (1 mentions)
Prism software 4, by GraphPad (1 mentions)
Igor pro 5.05a, by Wavemetrics (1 mentions)
Amos 19, by IBM (1 mentions)
Excel 2010, by MedCalc (1 mentions)
Prism v5, by GraphPad (1 mentions)
Chlorophyll meter spad 502plus, by Konica Minolta (1 mentions)
Sigmaplot 12, by Grafiti LLC (1 mentions)
297 protocols using spss 22.0 statistical
1
Quantitative Analysis of GFP Expression
2
Multivariate Analysis of Prognostic Factors
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Data were tabulated, and statistical analyses were performed using SPSS 22.0 statistical software (IBM Corp., Armonk, NY, USA). The statistical significance between all comparisons of clinicopathological features was examined using χ2 analysis. The time from the first diagnosis date to the date of mortality or the last day of the follow-up assessment was plotted as the overall survival time. The period from therapy to local recurrence or metastasis was considered the period of disease-free survival. The survival rate curves were analysed using the Kaplan-Meier method, and the log-rank test was used to evaluate the significance of the differences. The significance of variables for survival rates was analysed using the Cox proportional hazards model in univariate and multivariate analyses. The data from the in vitro studies were assessed through unpaired Student's t-tests. Each assay was conducted in triplicate and repeated three times. All the cases were two-sided and presented as the mean ± standard deviation, and P<0.05 was considered to indicate a statistically significant difference.
3
Statistical Analysis of Tumor Survival
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The p-values and R2 values of the data were analyzed using SPSS 22.0 statistical analysis software (IBM Corporation, New York, USA). The p-values were analyzed by the chi-square test or Fisher’s test, and the R2 values were analyzed by the Pearson correlation coefficient. tumor-specific survival was calculated using the Kaplan-Meier method. A p-value < 0.05 indicated a significant difference.
4
Comparative Gene Expression Analysis
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All data are expressed as mean ± SEM, and statistical analysis was performed using the SPSS 22.0 statistical software (IBM, Chicago, Illinois). The experimental data were analyzed by one-way analysis of variance. Student's paired t-test was used to compare qPCR results, and P values < 0.05 were considered statistically significant. GO Analysis was based on the GO database. Fisher's exact test and multiple comparison test were used to calculate the significance level (P value) and false positive rate (FDR) of each function. P value < 0.05 was the criterion for significance screening. Pathway analysis was based on the KEGG database, and Fisher's exact test and chi-square test were used for the DEGs. A pathway in which the target gene participated in was analyzed for significance and selected according to P value < 0.05.
5
Evaluating Experimental Treatment Effects
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All experiments were performed at least three times. Values are expressed as mean±S.E.M., and were analyzed by ANOVA followed by Bonferroni's multiple comparisons or unpaired t-test with SPSS 22.0 statistical software (IBM Corp., Armonk, NY, USA). P<0.05 was considered statistically significant.
6
Statistical Analysis of Experimental Data
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Data from each group were analyzed by one-way analysis of variance, followed by Tukey’s post hoc test, using SPSS 22.0 statistical software for Windows (IBM, Armonk, NY, USA). The data showed a normal distribution and were homogenous. Data are presented as the mean ± standard error of the mean (SEM). A value of P < 0.05 was considered significant.
7
Diurnal Variation in Physiological Metrics
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All numerical values are given as mean ± SD, median ± IQR (Interquartile range), and percent as appropriate. Distribution normality was determined by Kolmogorov–Smirnov and Shapiro–Wilk tests as appropriate. Students' t, paired-t, Mann–Whitney U, chi-square and exact tests were used appropriately according to the numerical/categorical or paired/independent character of the data. Correlation analysis was performed with the Pearson test. The Pearson correlation coefficient (r) between 1 and 0.8 was categorized as "very strong", 0.6 to 0.8 as "strong", 0.6 to 0.4 as "moderate", 0.4–0.2 as "weak" and less than 0.2 as “negligible (or very weak)".Diurnal variation of the variables was tested with analysis of variance for repeated measures. In this hour-based 24-h long analysis, the Greenhouse–Geisser method was used appropriately for testing within-subjects effects and the Bonferroni method for adjustment of confidence intervals for multiple comparisons. The significance level for the p value in correlation analysis was accepted as 0.012 after Bonferroni correction. In other evaluations, p value lower than 0.05 was set as the statistical significance level. SPSS®22.0 statistical package-program (IBM SPSS Statistics for Windows, IBM Corp., Armonk, NY) was used for the analyses.
8
Comparative Analysis of Biomarker Profiles
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All experiments were repeated at least thrice. Data were represented as means ± standard deviation; the SPSS 22.0 statistical software (IBM Corp., Armonk, New York, USA) was used to determine significant differences between the groups. Multiple sample means were compared using analysis of variance, and pair comparisons among multiple groups was performed using the Student–Newman–Keuls test. Statistical significance was set at p < 0.05.
9
Spatial Memory Assessment in Rodents
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All values are presented as mean ± standard deviation (SD). Multiple group means were compared by one-way or two-way ANOVA, followed by post hoc Tukey’s tests for pair-wise comparisons. Group and training day differences in MWM escape latencies were compared by repeated-measures ANOVA. All analyses were performed using SPSS 22.0 statistical software (IBM, USA). A P value <0.05 was considered statistically significant for all tests.
10
Statistical Analysis of Non-Parametric Data
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All statistical analyses were performed using IBM SPSS 22.0 statistical software (IBM Corp. Released 2013. IBM SPSS Statistics for Windows, Version 22.0. Armonk, NY: IBM Corp.c., Chicago, IL, USA). Descriptive statistics were calculated and reported for all measures. The Kolmogorov–Smirnov test and Shapiro–Wilk test were used to assess the distribution of the data. Median and range were used for the description of non-parametric data, while differences between groups were calculated with the Mann–Whitney U Test as appropriate.
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