SPSS 19.0 statistic software (SPSS Inc., Chicago, IL, United States) was used to perform the statistical analysis. Year and biochar application were assumed to be fixed factor and the replicates were assumed to be random factors. Error bars in the figures represent standard errors of the mean. Least significant differences were used to separate treatment means at the 5% probability level. Regression analysis was used to evaluate the relationships between leaf nitrogen content and net photosynthetic rate, net photosynthetic rate and peanut yield. The responses of chlorophyll fluorescence parameters, gas exchange parameters, leaf nitrogen content, yield, and yield components to biochar application were further analyzed with the principal component analysis in R studio version 1.1.442 using the Factoextra package (Kassambara, 2015 ).
Spss 19.0 statistic software
Manufactured by IBM
Sourced in United States
SPSS 19.0 is a statistical software package developed by IBM. It provides advanced analytical capabilities for data management, analysis, and presentation. The software is designed to handle a wide range of data types and can be used for tasks such as descriptive statistics, regression analysis, and data visualization.
Automatically generated - may contain errors
Lab products found in correlation
4 protocols using spss 19.0 statistic software
1
Biochar's Impact on Peanut Productivity
2
Statistical Analysis of Biomedical Data
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
Continual data are expressed as means ± standard deviations, medians, and inter-quartile ranges, dependent on their distribution. Categorical data are expressed as the real counts and percentages. The difference between groups over a period was analyzed by repeated measurement using a mixed-effects model or analyzed by t test, Wilcoxon rank sum test or Wilcoxon matched-pairs signed rank sum test, or Fisher’s exact test. Survival curves were plotted using the Kaplan-Meier method and were compared by the log-rank test. Statistical analyses were performed using SPSS 19.0 statistic software (SPSS Inc., Chicago, IL). A p value of <0.05 was considered statistically significant.
3
Comparative Analysis of Clinical and Radiological Data
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
SPSS 19.0 statistic software (SPSS Inc., Chicago, Illinois, USA) was used for all statistical analyses in this study. Descriptive data are represented as means ± standard deviation. Clinical and radiological data pre-, postoperative were compared using the paired t test. A p value of less than .05 was considered to be statistically significant.
4
Assessing WMH Impact on Cognitive Decline
Check if the same lab product or an alternative is used in the 5 most similar protocols
+ Expand
We used t-test and one way-ANOVA for continuous variables normally distributed, Wilcoxon-Mann-Whitney test for continuous variables without normal distribution and chi-square test for categorical variables. Liner mixed-effects models for repeated measure were used to analyze the association of the severity of WMHs with MMSE scores. WMH scores were square root transformed before entering the liner mixed-effects model. The model included WMH scores at baseline, follow-up time, and the interaction between WMH scores and follow-up time. The estimated effect of the interaction term reflects the impact of the WMH scores on the annual change of MMSE score. 16 Model 1 was adjusted for age, sex, and education level. Model 2 was further adjusted for smoking, alcohol, depression, hypertension, diabetes, hyperlipidemia, brain infarcts, brain atrophy, apoE ε4 status, and baseline MMSE scores. The relation between subcortical WMH lesions and annual MMSE decline was further conditional on the severity of periventricular WMHs and vice versa. 17 All analysis was performed by SPSS 19.0 statistic software (SPSS Inc., Chicago, IL, USA).
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!