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Spss 17.0 system

Manufactured by IBM
Sourced in United States

SPSS 17.0 is a data analysis software system. It provides tools for data access, data management, and statistical analysis. The core functions of SPSS 17.0 include data manipulation, analysis, and presentation of results.

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Lab products found in correlation

6 protocols using spss 17.0 system

1

Survival Analysis of THOP1 in Cancer

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Statistical analysis of data was performed by SPSS 17.0 system. Chi-square test was performed to examine the association of THOP1 and various clinicopathologic factors. Follow-up time was censored if the patient was lost to follow-up. Survival curves were drawn using the Kaplan–Meier method and compared by the log-rank test. Multivariate Cox regression analysis was used to identify significant independent prognostic factors. All data are mean ± standard deviation (SD) from independent assays. Other statistical analyses were performed using a Student’s t-test. P<0.05 was considered to be statistically significant.
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2

Analyzing Experimental Data Rigorously

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The data are presented as the means (±SD) or medium (95% CI range). The difference between the values amongst the different time points and groups was determined with ANOVAs for normally distributed data or Kruskal–Wallis tests for skewed data. Statistical analysis was performed with the SPSS 17.0 system. P < 0.05 for two tails was considered statistical significance.
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3

DVT Risk Factors and Predictors

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Statistical analysis was performed using SPSS 17.0 system software (SPSS Inc., Chicago, IL, USA). Numeric data were shown as mean ± standard deviation. Categorical data were shown as numbers with percentages. Categorical variables including gender, hypertension, insulin resistance, smoking history, malignancy, heart disease, and thrombosis history were compared by a chi-square test. Continuous variables including age, BMI, LMR, and MHR were analyzed by the Student t-test. The association of LMR or MHR with total DVT or symptomatic DVT was investigated using multiple logistic regression after adjustment for other variables. The OR (odd ratio) and 95% CIs (confidence intervals) were calculated for each associated variable. ROC (receiver-operating characteristic) curve was performed by MedCalc 11.5 (MedicReS, New York, NY) to identify the sensitivity and specificity of postoperative Hb (hemoglobin) and perioperative LMR and MHR for predictive value of DVT. P < 0.05 was considered significant in all statistical analysis.
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4

Statistical Analysis of Experimental Data

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SPSS17.0 system (Chicago, IL) was used to analyse the data. All data were expressed as mean ± standard error of mean (S.E.M.) or percentage. Differences among groups were analysed by a one-way analysis of variance (ANOVA) followed by Dunnett’s test. p Value less than or equal to 0.05 was noted as statistically significant.
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5

Multivariate Analysis of mRNA Levels in Multiple Myeloma

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The data were presented as mean ± SD. All statistical analyses were performed using the SPSS 17.0 System. Comparison of mRNA levels between healthy controls and different MM subtypes was using a Student’s t test, one-way analysis of variance (ANOVA) was used to assess multiple pairwise comparisons p < 0.05 was considered statistically significant. Estimation of PFS was performed using the method of Kaplan and Meier.
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6

Quantitative Analysis of Cell Viability

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All experimental data were expressed as means ± standard error (SEM.) or percentage and analyzed for statistical significance using one-way analysis of variance (ANOVA) followed by Dunnett's test. Tests were performed using SPSS 17.0 system (Chicago, IL); p value less than or equal to 0.05 was considered to be statistically significant.
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