Data from the behavioral tests were analyzed by ANY-maze, POLY File (Imetronic, Pessac, France), SPSS (IBM SPSS Statistics 20) and GraphPad (Prism 5.0). Data were compared using student’s unpaired t-test and one-way and two-way analysis of variance (ANOVA) followed by the Bonferroni post hoc test. Comparisons of proportions of individuals in the gambling task were conducted using the non-parametric Mann–Whitney test. The neural data were processed off-line using NeuroExplorer 5 (Plexon, Dallas, TX) and exported to custom written MATLAB (MathWorks, Natick, MA) programs for additional analysis. Data sets were compared by one-way repeated-measures ANOVA followed by multiple comparisons of Bonferroni’s test using Prism 5.0 (GraphPad, La Jolla, CA). Results were expressed as mean ± SE. P < 0.05 was considered statistically significant.
Spss statistics 20
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Sourced in United States
SPSS Statistics 20 is a software package developed for statistical analysis. It provides a wide range of statistical and data management capabilities, including descriptive statistics, bivariate and multivariate analysis, and modeling tools. The software is designed to help users analyze and interpret data efficiently.
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Lab products found in correlation
Prism 8, by GraphPad (16 mentions)
Prism 6, by GraphPad (12 mentions)
Prism 5, by GraphPad (12 mentions)
Prism 9, by GraphPad (3 mentions)
Prism 7, by GraphPad (3 mentions)
Spss statistics 20, by IBM (2 mentions)
Matlab, by MathWorks (1 mentions)
Neuroexplorer 5, by Plexon (1 mentions)
Instat 3, by GraphPad (1 mentions)
Prizm 5.0 statistical analysis software, by GraphPad (1 mentions)
Prism v6, by GraphPad (1 mentions)
Imagej, by FlowJo (1 mentions)
Prism v9, by GraphPad (1 mentions)
Statistica 7, by GraphPad (1 mentions)
Prism 6.0f, by GraphPad (1 mentions)
Excel 2011, by IBM (1 mentions)
Matlab r2017a, by GraphPad (1 mentions)
Prism v8, by GraphPad (1 mentions)
Prism v5, by GraphPad (1 mentions)
80 protocols using spss statistics 20
1
Behavioral and Neural Data Analysis
2
Raman Spectroscopy Biomarkers for MDS and AML
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Patients with MDS, AML patients, and healthy controls
all had their blood Raman spectra analyzed using supervised OPLS-DA
performed in SIMCA 14.1. The OPLS model’s efficacy was measured
by the goodness of fit metrics R2 and Q2. Under the null hypothesis, we randomly changed
the Y matrix 200 times and resampled the data to
see how well the model held up. Raman peaks of statistical significance
were identified as potential biomarkers using a classification model
that included cluster analysis and V + S analysis. On the basis of
the V + S plot’s correlation coefficient, loadings, and distance
from the center, the peak site of a potential biomarker was selected
as a VIP > 1.0. The collected candidates for biomarkers were subjected
to a significance test, and those that had a P value
lower than 0.05 were deemed to have high clinical utility. Processing
of pertinent data was done in Origin. Statistics were analyzed using
IBM SPSS Statistics 20, and graphics were created with GraphPad Prism
5.Figure 5 depicts
the conceptual framework for this study, which includes the collection
of serum samples, the detection of Raman spectra, multivariate analysis,
and the construction of the identification model.
all had their blood Raman spectra analyzed using supervised OPLS-DA
performed in SIMCA 14.1. The OPLS model’s efficacy was measured
by the goodness of fit metrics R2 and Q2. Under the null hypothesis, we randomly changed
the Y matrix 200 times and resampled the data to
see how well the model held up. Raman peaks of statistical significance
were identified as potential biomarkers using a classification model
that included cluster analysis and V + S analysis. On the basis of
the V + S plot’s correlation coefficient, loadings, and distance
from the center, the peak site of a potential biomarker was selected
as a VIP > 1.0. The collected candidates for biomarkers were subjected
to a significance test, and those that had a P value
lower than 0.05 were deemed to have high clinical utility. Processing
of pertinent data was done in Origin. Statistics were analyzed using
IBM SPSS Statistics 20, and graphics were created with GraphPad Prism
5.
the conceptual framework for this study, which includes the collection
of serum samples, the detection of Raman spectra, multivariate analysis,
and the construction of the identification model.
3
Statistical Analysis of Touch Response
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Two sample comparisons were performed using Student’s t test and three sample comparisons using analysis of variance (ANOVA) followed by Dunnet’s t post hoc test (IBM SPSS Statistics 20 and GraphPad Prism version 6.05). To improve the fit of data into the normal distribution, the touch response data presented in Figure 6 , G and H, were subjected to transformation by natural logarithm prior to ANOVA and Dunnet’s t post hoc test. Columns in figures indicate average + standard error.
4
Diurnal Metabolic Regulation in Mice
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For all experiments, we used at least three animals for every time point for each feeding type and each genotype. Data are shown as average ± SD. IBM SPSS Statistics 20 and GraphPad Prism Version 5.04 software packages were used for statistical analysis. To assay the effects of genotypes and the time of the day, the analysis was performed using two-way or one-way analysis of variance, followed by pairwise comparison of genotypes over time. p < 0.05 was considered as a statistically significant difference.
5
Comparative Analysis of Biological Variables
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For descriptive purposes, continuous variables which were deviated from the normal distribution according to the results of Shapiro-Wilk tests, are given as median and 25th–75th percentiles. For categorical variables numbers and percentages were used. Non-parametric tests as Mann-Whitney U test or Kruskal-Wallis test with Dunn’s post hoc test were used for group comparisons in case of continuous variables. For categorical variables Pearson’s χ2 test was performed.
For cluster analysis hierarchical clustering by Ward method with squared Euclidean distances was used.
For the statistical analysis IBM SPSS Statistics 20 and Graph Pad Prism 5 software was used. Two-tailed p-values were calculated and the significance level was determined at a value of p < 0.05, if not otherwise stated.
For cluster analysis hierarchical clustering by Ward method with squared Euclidean distances was used.
For the statistical analysis IBM SPSS Statistics 20 and Graph Pad Prism 5 software was used. Two-tailed p-values were calculated and the significance level was determined at a value of p < 0.05, if not otherwise stated.
6
Epigenetic Regulation of Body Composition
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The statistical analysis was carried out using IBM SPSS Statistics 20 and GraphPad Prism 6. All data are represented as mean ± standard deviation (SD). Paired t-tests were used to analyze the different time points for parametric and Wilcoxon tests for nonparametric values. Correlations between methylation, miRNA expression, and body composition were tested using Pearson correlation and linear regression. Correlations between dietary habits, methylation, and mtDNA were tested using Spearman’s Rho correlation and Kendall’s tau. A p-value less than or equal to 0.05 was defined as significant for all tests.
7
Statistical Analysis of Experimental Data
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IBM SPSS Statistics 20, GraphPad Prism 8, Medclac application was used for data analysis. The differences between the two groups of normal distribution data were verified by the independent t-test, the classified data were analyzed by the chi-square test, and the Kaplan-Meier test was used to verify the differences in the survival curve. P<0.05 was considered to have significant differences between the two groups of data.
8
Instrument Safety and Needle Stick Injuries
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Data on reported needle stick injuries and data on delivered safe and unsafe instruments from the central pharmaceutical facility were anonymously entered into a Microsoft Excel 2010 database and further analyzed using the statistical software IBM SPSS statistics 20.
The GraphPad Instat 3.06 software was used for assessments by linear regression of correlation between use of unsafe instruments and the incidence of injuries due to the respective instruments. ANOVA analysis was performed to confirm that the slope differed from zero. P values <0.05 were considered significant.
The GraphPad Instat 3.06 software was used for assessments by linear regression of correlation between use of unsafe instruments and the incidence of injuries due to the respective instruments. ANOVA analysis was performed to confirm that the slope differed from zero. P values <0.05 were considered significant.
9
Circadian Rhythms in Gene Expression
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For all experiments, at least three male or female mice for every time point and for each feeding type were used (N = 3). Data are shown as average +/− standard error of mean. IBM SPSS Statistics 20 and GraphPad Prism Version 5.04 software packages were used for statistical analysis. To assay the effects of sex, diet and the time of the day, the analysis was performed using two-way repeated ANOVA. If the effect of feeding, time or sex was found to be statistically significant Bonferroni correction was used to calculate p-value for pairwise comparison. P < 0.05 was considered as a statistically significant difference. For the analysis of Circadian Rhythms in gene expression “R” Version 3.2.5 software – Cosinor Analysis package was used and the results are summarized in the Supplementary Tables S2 and S3 .
10
Quantitative Data Analysis Protocol
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Normally distributed quantitative data were presented as mean ± standard, while the nonnormally distributed data were expressed as interquartile range. 1-way ANOVA test was used for assessment of the differences among values during the course of treatment, and Mann–Whitney U tests or unpaired t-test was used for comparison between patients and healthy controls. All data were analyzed by SPSS Statistics 20 and all figures were made by Prizm5.0 statistical analysis software (GraphPad Software). P value less than 0.05 was considered to be statistically significant.
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