The statistical analysis was done using Statistical Package for the Social Sciences version 17.0 software for Windows (SPSS Inc., Chicago, IL, USA) using descriptive and inferential statistics. The main outcome measures were the proportion of respondents who had good knowledge of interdisciplinary team working and the proportion that had a good attitude toward interdisciplinary team working. Frequencies of different responses were expressed as percentages. Tests of association were done using the Pearson’s chi-square test. A P-value of ≤0.05 was considered to be statistically significant.
Statistical package for the social sciences version 17.0 software for windows
Manufactured by IBM
Sourced in United States
The Statistical Package for the Social Sciences (SPSS) version 17.0 for Windows is a software suite designed for statistical analysis. It provides tools for data manipulation, analysis, and presentation, catering to the needs of researchers and professionals in the social sciences and beyond.
Automatically generated - may contain errors
Lab products found in correlation
4 protocols using statistical package for the social sciences version 17.0 software for windows
1
Assessing Interdisciplinary Team Perspectives
2
Statistical Analysis of Experimental Data
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
We used χ2 tests to analyze the experimental data. Statistical Package for the Social Sciences version 17.0 software for Windows (SPSS Inc, Chicago, IL, USA) was used for all statistical analyses. A P-value <0.05 was considered to be statistically significant.
3
Genetic Variants and Biomarker Correlations
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
The results were first presented as the geometric mean and 95% CI (confidence interval) for continuous variables. Categorical variables were expressed as number and percentage. Allele frequencies were estimated using the gene counting method, and Hardy-Weinberg equilibrium was determined for all genotypes using the χ2 test. The differences on biomarkers concentrations were analyzed by Mann-Whitney or Kruskall-Wallis tests. For all the statistical analysis, variant homozygous and heterozygous genotypes were considered together and compared with the wild type, except for rs713041 in GPX1, which had a higher variant allele frequency. Linear regression was used to investigate how the biomarkers were correlated. Differences were considered significant at p < 0.05. The analyses were performed using the Statistical Package for the Social Sciences software version 17.0 for Windows (SPSS, Chicago, IL, USA) and GraphPad Prism (GraphPad Prism version 5.00 for Windows, GraphPad Software, San Diego, CA, USA).
4
Statistical Analysis of Cancer Progression
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
Data were analyzed using the Statistical Package for the Social Sciences software, version 17.0, for Windows (SPSS Inc.). Student's t-test was used to compare two groups consisting of normally distributed interval data. One-way ANOVA and Kruskal-Wallis tests were used to compare three or more groups when interval data was normally distributed and not necessarily normally distributed, respectively. Frequency distributions between categorical variables were compared using the chi-square test and Fisher's exact method. OS and PFS were estimated according to the Kaplan-Meier method and compared using the log-rank test. To assess potential associations between FOXM1 overexpression and cancer progression or death, hazard ratio and confidence intervals were estimated by Cox proportional hazard regression models. P < 0.05 (two-sided) was considered significant.
About PubCompare
Our mission is to provide scientists with the largest repository of trustworthy protocols and intelligent analytical tools, thereby offering them extensive information to design robust protocols aimed at minimizing the risk of failures.
We believe that the most crucial aspect is to grant scientists access to a wide range of reliable sources and new useful tools that surpass human capabilities.
However, we trust in allowing scientists to determine how to construct their own protocols based on this information, as they are the experts in their field.
Ready to get started?
Sign up for free.
Registration takes 20 seconds.
Available from any computer
No download required
Revolutionizing how scientists
search and build protocols!