Spss statistics 13

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SPSS Statistics 13.0 is a software package used for statistical analysis. It provides a comprehensive set of tools for data management, analysis, and presentation. The software is designed to handle a wide range of data types and offers a variety of statistical techniques, including regression analysis, factor analysis, and cluster analysis.

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Lab products found in correlation

Originpro 2022, by OriginLab (1 mentions) Spss 22, by IBM (1 mentions) Spss statistics 27, by IBM (1 mentions) Prism 9, by GraphPad (1 mentions) Iq5 detection instrument, by Bio-Rad (1 mentions)

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SPSS 13.0 statistic SPSS 13.0 statistic software SPSS Statistics v. 13.0 software SPSS statistics software for Windows, version 13.0 SPSS Statistics software package version 13 SPSS Statistics software version 13.0 SPSS Statistics version 13.0 SPSS Advanced Statistics 13.0 SPSS 13.0 statistics software SPSS Statistics 13.0 for Windows

38 protocols using spss statistics 13

Analytical Parameter Stability in Packaging

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Statistical analyses were performed to assess the effect of packaging and storage conditions on the analytical parameters. The significance of differences was estimated by analysis of variance (ANOVA). The statistical significance level was set to 0.05. Statistical analyses were performed using SPSS^® Statistics 13.0 (IBM, Armonk, NY, USA).
Results are presented as mean value ± standard deviation. Data were analyzed through Spearman’s correlation to have a measure of the strength and direction of the association or relationship between the concentrations of analytical parameters and time of storage under different CWF lamp, and time of storage under different temperatures. All pairwise comparisons were run at 95% confidence intervals and p-values were Bonferroni adjusted through the statistical package SPSS^® Statistics 13.0 (IBM, Armonk, NY, USA).

Arena E., Rizzo V., Licciardello F., Fallico B, & Muratore G. (2021). Effects of Light Exposure, Bottle Colour and Storage Temperature on the Quality of Malvasia delle Lipari Sweet Wine. Foods, 10(8), 1881.

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Consistency of Radiographic and Pathologic Grading

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The consistency of radiographic and pathologic grading as well as the consistency of CT and MRI grading based on the histologic examination were evaluated by consistent percentage and weighted kappa statistics. The kappa scores were classified into six categories: less than 0.00 (poor), 0.00 to 0.20 (slight), 0.21 to 0.40 (fair), 0.41 to 0.60 (moderate), 0.61 to 0.80 (substantial), and 0.81 to 1.00 (almost perfect) [15 (link)].
All radiographic and pathologic grading was assessed by two independent professionals. Grading was reevaluated up to 4 weeks after the first assessment. The interobserver and intraobserver agreement was estimated. The sensitivity, specificity, false negative rates (FNR).and false positive rate (FPR) were also calculated. SPSS (SPSS Statistics 13) was used for the statistical analyses.

Zhou X., Liu Y., Zhou S., Fu X.X., Yu X.L., Fu C.L., Zhang B, & Dai M. (2016). The correlation between radiographic and pathologic grading of lumbar facet joint degeneration. BMC Medical Imaging, 16, 27.

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Genetic Analysis of Patient Data

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Statistical analysis was performed with SPSS Statistics 13 (SPSS Corporation, Chicago, IL). Continuous variables were presented as mean ± standard deviation and comparisons in 2 groups were performed using Student t test. Categorical variables, the Hardy–Weinberg equilibrium of the polymorphisms, and genotype/allele frequencies were presented with the number (percentage) and tested with the chi-squared or Fisher exact test. SHEsis software (http://analysis2.bio-x.cn/SHEsisMain.htm) was used to compare the allele frequencies and haplotype frequencies. The Haploview 4.2 software was used to calculate pairwise linkage disequilibrium (LD) of SNPs and construct haplotype blocks. The sample size and statistical power was determined using the Genetic Power Calculator (http://pngu.mgh.harvard.edu/purcell/gpc/cc2.html). The data from the case report forms were compiled as a dataset loading into a database and validated prior to the statistical analysis. The database, constructed using SQL server, contains the data pertaining to the SNPs, clinical features and treatment, and clinical follow-up of patients.

Yang H.W., Xie Y., Zhao Y., Sun L., Zhu X., Wang S., Zhang Y.Q., Lei P, & Meng Y. (2017). TNFAIP3 gene rs7749323 polymorphism is associated with late onset myasthenia gravis. Medicine, 96(20), e6798.

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Quantifying G4 DNA Enrichment

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For both the G4DP experiments performed in vitro and in vitro, 2 μL of input and precipitated DNA (3 ng/μL each) was used as template. The enrichment of precipitated DNA was calculated by using the 2^(ΔΔCt) method and expressed as fold-change over the input. Each experiment was repeated three times; all primer sequences are listed in Tables S2 and S8. Significance test was performed by using One-way Anova analysis in SPSS Statistics 13 program, which p-value < 0.05 means significant (p < 0.001 ∗∗∗, P < 0.01 ∗∗ and p < 0.05 ∗).

Feng Y., He Z., Luo Z., Sperti F.R., Valverde I.E., Zhang W, & Monchaud D. (2023). Side-by-side comparison of G-quadruplex (G4) capture efficiency of the antibody BG4 versus the small-molecule ligands TASQs. iScience, 26(6), 106846.

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Multivariate Analysis of Baking Volatiles

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Data for each chemical parameter were submitted to an ANOVA (SPSS^® Statistics 13.0, Armonk, NY, USA) to evaluate the significant differences (p < 0.05) within samples baked at the same temperature and for the same time.
Microsoft XLstat software 2014 (Addinsoft, Paris, France) was used to perform the statistical analysis of the volatile data. ANOVA, Tukey’s test, and principal component analysis (PCA) were performed to understand the statistically significant differences and investigate the relationship between sugar formulations, baking conditions, and aroma volatiles. A heat map was generated to visualise the clustering of the multivariate data.

Cincotta F., Brighina S., Condurso C., Arena E., Verzera A, & Fallico B. (2021). Sugars Replacement as a Strategy to Control the Formation of α-Dicarbonyl and Furanic Compounds during Cookie Processing. Foods, 10(9), 2101.

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Statistical Analysis of Survival Data

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All data were analyzed using the SPSS Statistics 13.0 software. Data are expressed as means ± standard deviations (SDs). Statistical analyses were carried out by analysis of variance (ANOVA) followed by appropriate post hoc tests, including multiple comparison tests (least significant difference). Cumulative survival were carried out by an analysis of the log rank test (Kaplan–Meier). P-values < 0.05 were considered statistically significant.

Liu D., Yin Z., Huang Q., Ren Y., Li D., Wang L., Cui S., Zhang Y., Ning Y., Lun L., Cai G., Bai X., Sun X, & Chen X. (2019). Exogenous biological renal support ameliorates renal pathology after ischemia reperfusion injury in elderly mice. Aging (Albany NY), 11(7), 2031-2044.

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Circulating Cell-Free DNA and Mitochondrial DNA Analysis in Breast Cancer

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All statistical analyses were performed using SPSS statistics 13.0 software (SPSS, Inc.). Statistical differences between ccfnDNA or ccfmtDNA concentrations and the ccfmtDNA/ccfnDNA ratio were compared using ANOVA followed by Bonferroni's post-hoc test. The Kolmogorov-Smirnov test confirmed that the data were normally distributed. The correlation of the mean values with other parameters was assessed by calculating Pearson's and Spearman's correlation coefficients. Student's t-test was used to determine the association of ccfnDNA, ccfmtDNA or the ccfnDNA/ccfmtDNA ratio with menopause, smoking and lymph node status, while Pearson's correlation was used to study the correlation between ccfnDNA, ccfmtDNA and ccfnDNA/ccfmtDNA levels with age and tumor size. Furthermore, Spearman's correlation analysis was used to study the correlation between ccfnDNA, ccfmtDNA and ccfnDNA/ccfmtDNA levels with the tumor stage or grade, or with the ER, PR and Her2/neu receptor status. P<0.05 was considered to indicate statistical significance.

Safi M, & Najib A.R. (2020). Evaluation of circulating cell-free nuclear and mitochondrial DNA levels in Syrian patients with breast tumor. Experimental and Therapeutic Medicine, 21(1), 65.

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Statistical Analysis of Hepatic Vein Pressure Gradient

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Statistical analysis was performed using SPSS statistics 13.0. Data were expressed as mean or median values, ranges, and percentages. Univariate analysis was performed by the Student t test or χ² test. In multivariate analysis, the value of HVPG was correlated to the serological tests using the linear regression analysis. The survival rates were analyzed by the Kaplan-Meier test. P values <0.05 were regarded as the valid significance in statistics. The value of R², by the regression analysis, determined the reliability of the regression equation. The fitness of the regression model has been validated by the residual plots and analysis of variance (ANOVA) with F-statistics. Sensitivity and specificity for the potential diagnostic performance to predict PHT by cHVPG were assessed by receiver operating characteristic (ROC) curve.

Kim T., Kim B.W., Wang H.J., Lee H.Y., Won J.H., Kim J., Hu X.G., Sim J., Bang J.B, & Kim Y.B. (2015). Quantitative Assessment of the Portal Pressure for the Liver Surgery Using Serological Tests. Annals of Surgery, 264(2), 330-338.

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Statistical Analysis of Continuous and Categorical Data

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Data were expressed as mean± one standard deviation, or median (range) as appropriate. Mann Whitney U test or t test were used for comparison of continuous variables between groups. The significance of the correlation between parameters was assessed using Spearman rank as the data was not normally distributed. Categorical data were compared using the chi-square test. Multivariate analysis used multiple linear regression analyses. Statistical analyses were carried out using SPSS Statistics 13.0 (SPSS Inc., USA). A p value less than 0.05 was considered statistically significant, and all p values were two sided.

Yang G., Liu R., Peng P., Long L., Zhang X., Yang W., Tan S., Pan H., Long X., He T., Anderson L, & Lai Y. (2014). How Early Can Myocardial Iron Overload Occur in Beta Thalassemia Major?. PLoS ONE, 9(1), e85379.

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Statistical Analysis of Experimental Data

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All statistical analyses were performed using SPSS Statistics 13.0 (Chicago, IL, USA). Data were presented as mean ± SEM of at least three independent experiments and statistical significance of the differences between groups was calculated using the Student’s t test. All tests were two-sided and P < 0.05 was considered as statistically significant.

Wu F., Qin Y., Jiang Q., Zhang J., Li F., Li Q., Wang X., Gao Y., Miao J., Guo C., Yang Y., Ni L., Liu L., Zhang S, & Huang C. (2019). MyoD1 suppresses cell migration and invasion by inhibiting FUT4 transcription in human gastric cancer cells. Cancer Gene Therapy, 27(10), 773-784.

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