Spss 21 statistical

The experimental data were analyzed using SPSS 21 statistical software. All data were expressed as the mean ± the standard error of the mean (SEM).Significant differences among the groups were determined by a one-way analysis of variance and post hoc testing was performed for inter-group comparisons for least significant differences (LSDs) using a statistical analysis program for social science (SPSS).

All data were tested for normal distribution and homogeneity of variance using Kolmogorov–Smirnov test and Levene test, respectively. Independent sampled t-tests were performed to detect differences in behaviors and growth between the two experimental groups. All data analyses were conducted with SPSS 21 statistical software. A probability level of P < 0.05 was considered as significant.

Prior to EFA, Kaiser-Meyer-Olkin (KMO) was calculated to ensure that the sample size was adequate. KMO shows values between 0 and 0.49 as unacceptable, 0.5–0.7 as mediate; 0.7–0.8 as good, 0.8–0.9 as great, and > 0.9 as excellent [31 (link)]. EFA was performed using the principal component analysis with varimax solution [32 (link)]. Since we could not find a clear relationship between the items in the questions and the construct to be measured, we needed an exploratory factor analysis. In other words, we were not sure which items measured which structures. Therefore, because of this suspicion, we used exploratory factor analysis [33 ]. To select the factors, an eigenvalue greater than 1 and a factor loading equal to or greater than 0.4 were used. All the statistical analyses were performed using SPSS 21 statistical software package.