Statistics 16

Three separate batches of ground pork were prepared (repeated), and each batch of ground pork was determined in triplicate. Data were analyzed statistically using the Statistix 8.1 software (Statistix 8.1, Analytical Software, St Paul, MN, USA), and presented as the mean ± standard deviations (SD). SPSS Statistics 16.0 was required to test the data for normality and variance homogeneity. The analysis of variance (ANOVA) with Tukey’s multiple comparisons was used to measure the significance of the treatment effects (p < 0.05).

Effects of cold or desiccating conditions on nematode mortality were analyzed
with SPSS Statistics 16.0. Data from repeated bioassays that were not
significantly different were pooled for analysis. Statistical analyses were
performed using one-way or two-way ANOVA, followed by Tukey’s multiple means
comparison procedure. Percentage data were arcsine transformed before analysis.
A P value < 0.05 was considered statistically
significant.

Data were presented as mean ± SEM. Statistical analysis was performed using predictive analytics software statistics 16.0 (SPSS Inc., Chicago, IL, USA). The experimental groups were compared using ANOVA with repeated measures on the behavior test. A Tukey post-hoc test was used to follow up with significant ANOVA results. Cohn's D was used to examine the effect size. The statistical significance of the effects of the experimental treatment was determined by comparing the areas under the curve (P < 0.05, Student's t-test).

Each experiment was independently performed 3 times. SPSS Statistics 16.0 software was used for data analysis, and the data are shown as mean ± SD. The statistical analysis between groups was carried out using Student's t-test, and P < 0.05 was considered to be statistically significant.

The data were processed using an analysis of variance (ANOVA) and a general linear model program. Statistics 8.1 (Analytical Software, St Paul, MN, USA) was used for all statistical analyses. Tukey multiple comparisons were employed to establish the effect’s significance (p < 0.05). Using SPSS Statistics 16.0, the data were examined for variance homogeneity and normality. All data are expressed as mean ± standard error (SE). The illustration was produced utilizing Sigmaplot 12.0 software.

Data from all experiments are presented as mean ± SEM. Statistical analysis was performed using predictive analytics software statistics 16.0 (SPSS Inc., Chicago, IL, USA). Comparisons across the experimental groups were performed using one-way analysis of variance (ANOVA). The results of behavior experiments were analyzed by repeated measures of variance. Statistical significance of the effects of the experimental treatment was determined by comparing the areas under the curve (p<0.05).

Following data collection and coding, analysis was conducted using SPSS Statistics 16.0 (2008). Independent t-test and paired t-test were used to compare mean scores of the intervention and control groups in the cognitive learning test and the CDMNS before and after the integrated teaching-learning method. Comparison of baseline parameters was performed with independent t-test and Analysis of variance. Given that the intervention and control groups had significant differences in GPA prior to the intervention, and the intervention group had a significantly higher GPA, analysis of covariance (ANCOVA) was employed.