Statistical analyses were performed using IBM SPSS statistic version 19. All numerical data were subjected to normality testing using Shapiro-Wilk test and expressed as mean ± standard deviation (SD) or median (inter quartile range) for normal and non-normally distributed data. Parametric tests including Student’s t-test was used for normally distributed data; whereas, Mann-Whitney U test was used for non-normally distributed data. The Wilcoxon rank sum test was used within the groups. For qualitative data, Chi-Square test and Fisher’s Exact test were used, and data for each group were compared using ANOVA and Kruskal Wallis test. A P value < 0.05 was considered significant.
Spss statistic version 19
Manufactured by IBM
Sourced in United States
SPSS Statistics Version 19 is a software package used for statistical analysis. It provides a comprehensive set of tools for data management, statistical modeling, and reporting. The core function of SPSS Statistics Version 19 is to enable users to analyze and interpret data effectively.
Automatically generated - may contain errors
Lab products found in correlation
5 protocols using spss statistic version 19
1
Statistical Analysis of Experimental Data
2
Analyzing Organ Associations in Cattle and Sheep
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
Data analysis was conducted using SPSS Statistic Version 19 (IBM, USA). Chi-square tests were used to determine the association between different organs (inspected esophagus and diaphragms in both cattle and sheep). p<0.05 was considered to be statistically significant.
3
Statistical Analysis of Research Data
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
SPSS v.26.0 (IBM SPSS Statistic Version19, Chicago, IL, USA) and R statistical software (v.4.2.2; https://www.r-project.org ) were used for statistical analysis. We used independent samples t-test for quantitative data, and Wilcoxon test, chi-square test and Fisher’s exact test for qualitative data. A two-sided p-value of < 0.05 was considered significant.
4
Genetic Variants and Disease Risk Analysis
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
The statistical analyses were performed using the SPSS software (IBM SPSS Statistic version19) and JavaStat (http://statpages.org/ ). Chi-square and Fisher's exact tests were used for univariate comparisons of allelic and genotypic frequencies of the SNP loci between the groups. Binary logistic regression was used to adjust the genotypic differences for the effect of age, gender, body mass index (BMI), diabetes, and smoking status. The genotype analyses were performed by comparing each genotype frequency to the pooled total of the other groups. The assembly and prediction of haplotypes for the IL10 SNP cluster were done by the software ‘Phase’ (33 (link)). All loci were in Hardy–Weinberg equilibrium. A statistically significant difference was defined when p was<0.05.
5
Scratch Depth and Surface Roughness Analysis
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
Data were not normally distributed so they were transformed to natural logarithms for analysis. A linear mixed model analysis was designed using the statistical package IBM SPSS Statistic Version 19 to determine whether the mean scratch depths and surface roughness (Rq) values were significantly different between the three stages described. Linear regression was used to assess the association between the changes in both the scratch depth and surface roughness from stage 1 to stage 2, and then from stage 2 to stage 3. Significance was set at the 0.05 probability level.
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!