Spss for mac version 24

Data are presented as the mean ± standard deviation (±SD). Before using parametric tests, the assumption of normality was verified using Kolmogorov–Smirnov. The use of one-way analysis of variance for repeated measures to examine the difference in the GPS metrics collected between days. When significant p values were observed within the data (p < 0.05), t-test paired comparisons were used in conjunction with Holm’s Bonferroni method. Differences in time motion with respect to the 3 independent variables were determined using the Student’s t-test (match location) and a one-way analysis of variance (opponent level and score). When a significant F-value was found, Bonferroni’s post hoc tests were applied. The level of statistical significance was set at p < 0.05. Analyses were performed using SPSS for Mac version 24.0 (SPSS Inc., Chicago, IL, USA).

The SPSS for Mac, version 24.0 (SPSS, Inc., Chicago, IL, USA) was used to analyze the results (Table S1). The normality of the data was checked by the Shapiro–Wilk test, and all data were distributed in a normal way (p > 0.05). The significance level of the difference between groups involved was determined by the ANOVA or independent t-test, with the Bonferroni test as a post hoc test, and p < 0.05 is considered statistically significant.

Statistical analyses were performed using SPSS for Mac version 24.0. Descriptive statistics, including means, medians and ranges, where appropriate, were calculated for all variables. Nonparametric statistics were applied with McNemar’s test to compare the differences between methods within the same patient group. A p value of < 0.05 was considered statistically significant, and the p values were adjusted by the Bonferroni method when appropriate. When tests of statistical significance were applied to compare the sensitivity, specificity and accuracy rates, patients with indeterminate test results were grouped with the negative results [28 (link)]. Considering the paired design, the estimated sample size was determined to be 52 using the methodology published by Alonzo et al. [29 (link)]. This sample size would allow 80% power to detect differences in sensitivity and specificity between cross-sectional imaging and EUS-FNA at the 5% (two-sided) significance level. The expected effect size was estimated from the results of the previous studies.

Data were expressed as mean ± SD. SPSS for Mac version 24.0 was applied for data analysis. Independent-sample t tests were performed, and P values were corrected using the “Benjamini–Hochberg” method [25 ] and presented as P_adj. P_adj-values less than 0.05 were considered to be statistically significant. All the experiments were conducted in triplicate.

The water parameters, growth parameters, innate-immune indexes, and expression of immune-related genes were statistically analyzed by one-way analysis of variance (ANOVA) to determine significant differences among the tested groups, and polynomial contrasts were further analyzed to determine the effects of Acinetobacter application at different doses. Student’s t-test was employed to indicate significant differences between the control and treatments using the Statistical Package for Social Science (IBM SPSS statistic version 26). All data were plotted using Microsoft Excel (MS Excel 2016), and the results are presented as the mean ± SD. Significant differences were considered when p < 0.05. Survival data from the challenge test against A. hydrophila (AQAH001) were used for Kaplan–Meier survival analysis using SPSS for Mac (version 24.0, Chicago, IL, USA). The level of statistical significance of survival rates between the control and treatment groups was indicated using Student’s t-test at the significance level of 0.05.