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Spss 19.0 statistical software package

Manufactured by IBM
Sourced in United States

SPSS 19.0 is a statistical software package developed by IBM. It is designed to perform a wide range of statistical analyses, including data management, data analysis, and data presentation. The software provides a comprehensive set of tools for descriptive statistics, hypothesis testing, multivariate analysis, and more.

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20 protocols using spss 19.0 statistical software package

1

Evaluating SKP2 and PDCD4 Expression

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Results were expressed as mean ± SD from at least three independent experiments. SPSS19.0 statistical software package (SPSS Inc.) was used for statistical analysis. Statistical differences between groups were assessed using the Student t test. Association between SKP2 and PDCD4 expression in breast cancer cell lines was evaluated by the Spearman rank correlation test. Association between SKP2 and PDCD4 expression in colorectal cancer tissue was evaluated by the Chi-square test. P < 0.05 was considered statistically significant.
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2

Atrial Fibrillation Recurrence Risk Analysis

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Continuous data were expressed as Mean ± SD and compared with use of Student t-tests. Categorical data were expressed as percents and compared with use of the Pearson’s chi-squared test, continuity correction chi-squared test or Fisher’s exact test, as appropriate. Risk estimations were evaluated using univariate and multivariate logistic regression models with the presence of AF recurrence as the dependent variable. The Bland-Altman method was used to compare the reproducibility of the two physicians to measure independent risk factors. All data were required to achieve a P <  0.05 to be considered as statistically significant. The SPSS 19.0 statistical software package was used to analyze these data.
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3

Statistical Analysis Protocols for In Vitro and In Vivo Studies

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The significance of the in vitro and in vivo data was determined using the Student t test (2-tailed). The 2-tailed χ2 test and Fisher exact test were used to determine the statistical significance of the covariate differences. Survival rates were calculated using the Kaplan–Meier method and the log-rank test was used to compare the survival curves. The Cox proportional hazards model was used to calculate multivariate HRs for the variables. A P value of less than 0.05 was considered to be statistically significant. All statistical analyses were carried out using the SPSS 19.0 statistical software package (SPSS Inc., Chicago, IL).
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4

Measuring Biomass and Chlorophyll in HTL-WW Treated Plants

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At 7, 14 21 days after HTL-WW treatment (DAT), three plants per treatments have been sampled for shoot biomass determination. At the same time points, SPAD index was measured with a MINOLTA chlorophyll meter (SPAD 502-Plus). The flower biomass was measured at the end of the experiment (after 21 days).
Data were analysed by test-t for pairwise comparison of means (at P < 0.05) using SPSS 19.0 statistical software package (SPSS Inc., Cary, NC, United States).
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5

Statistical Analysis of Experimental Outcomes

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All data are presented as the mean ± standard deviation (SD). SPSS 19.0 statistical software package (SPSS Inc., Chicago, IL, United States) was used to analyze the data. GPower 3.1 software package was used to determine the adequate sample size (significance level α = 0.05; desired statistic power 1-β = 0.8). Student’s t-test was used to determine significant differences between the two groups, and one-way ANOVA was adopted among multiple groups. Differences with a P-value less than 0.05 were considered statistically significant.
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6

Environmental Factors in Inflammatory Bowel Disease

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Each investigator coded most of the answers for computer analysis using standard rules. SPSS 19.0 statistical software package (SPSS Inc., Chicago, IL, USA) was used for analysis. Separate analyses were performed for UC cases and their matched controls and for CD cases and their matched controls. Descriptive variables are presented as medians (interquartile range, IQR), and categorical variables are presented as frequencies with percentages. Each environmental factor was first tested by univariate analysis with odds ratios (OR) and 95% confidence intervals (95% CI). In multivariate analysis, based on conditional logistic regression, variables with a p-value < 0.05 in the univariate analyses were proposed for entry into the model. Rates of ‘unsure’ responses were compared between cases and controls to assess for differential reporting. A p-value of < 0.05 was considered significant.
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7

Cadmium Stress Response in Plants

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All of the parameters described above were measured 90 days after the plants were subjected to soil Cd treatments. SPSS 19.0 statistical software package (SPSS, Chicago, IL, United States) were used in the study to perform the statistical analyses. For each treatment, the mean values with standard deviation (±SD) are shown in the figures and tables. The parameters were analyzed by one-way analysis of variance (ANOVA, p < 0.05), followed by Duncan’s multiple range tests. The graphs were created using Origin 9.0 software (Origin Lab, United States).
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8

Statistical Analysis of Survival Outcomes

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All statistical assays were performed by using SPSS 19.0 statistical software package (SPSS, Chicago, IL, USA). The differences between two groups or multiple groups was used the Student’s t-test, one-way ANOVAs or χ2 tests. Overall survival (OS) curves and disease-free survival (DFS) curves were plotted using the Kaplan-Meier method.
The statistical differences between survival curves were estimated by log-rank test. Univariate and multivariate cox regression analyses were also performed. P<0.05 was considered statistically significant.
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9

Statistical Analysis of Experimental Data

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All statistical analyses were performed using the SPSS 19.0 statistical software package (Chicago, IL, USA), and the data are expressed as the means ± standard deviation (SD). Student’s t-test or one-way ANOVA was used for comparison of differences between groups. A value of p < 0.05 was considered significant in this study.
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10

PTPRO Expression Prognostic Analysis

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All statistical analyses were performed using the SPSS 19.0 statistical software package (SPSS Inc., IL, United States). The differences in PTPRO expression immunoreactivity score were compared by the Mann-Whitney U test. The statistical significance of differences was evaluated with a t-test, and means, standard error, and 95% confidence intervals were calculated using GraphPad Prism 5 (GraphPad Software Inc., San Diego, CA). Correlations between PTPRO expression and clinicopathological factors were investigated using the χ2 test. The correlation coefficient between variables was performed using Spearman’s rank test. Survival curves were generated using the Kaplan-Meier estimates, and the statistical significance of differences between curves was evaluated by the log-rank test. Furthermore, hazard ratios (HR) and 95% confidence intervals (CI), which were computed from univariate and multivariable Cox proportional hazards regression models (approximate proportionality was verified by visual examination of the Kaplan–Meier estimates), were used to assess associations between relapse-free survival and clinicopathological characteristics. A p-value of less than 0.05 was considered to be significant, and all tests were 2-sided.
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