Mixed-Method Evaluation of Watershed Management by Bahram Mohammadi Golrang

Author:Bahram Mohammadi Golrang
Language: eng
Format: epub
Publisher: Springer International Publishing, Cham

Fig. 3.13Bartlett and Leven test details for participation in WMP in terms of main occupation

Fig. 3.14Bartlett and Leven test details for participation in WMP in terms of alternative occupation

To test the difference between different education, main and alternative occupation groups within each group, the Least Square Difference (LSD) test was utilized.

3.6.10 Assumption for ANOVA

Assumptions for analysis of variance (ANOVA) include randomization, normality, and homoscedasticity. The result of run test showed that p > 0.251. In fact, it means data were collected randomly. Normality is assessed by a P-P plot of the observations. The P-P plot obtained for this data set is shown in Fig. 3.1. Based on the plot; the observations appear to be normally distributed. In addition, one of the appropriate statistical methods, Kolmogorov–Smirnov, was used to test the normality of dependent variable of this research. The results indicated that there is statistical significance for normality of participation in WMP (p > 0.05). Consequently, this data set met the normality assumption. To consider homoscedasticity of groups, two tests (Bartlett and Leven) were used for education, main occupation and second occupation groups (Figs. 3.12, 3.13 and 3.14). Bartlett’s test is used when the data are normally distributed. Bartlett’s test is not robust to departures from normality and Levine’s test when the data come from continuous, but not necessarily normal distributions. This method considers the distances of the observations from their sample median against their sample mean, which makes the test more robust for smaller samples. Results reveal that there is statistical significance for homoscedasticity of participation among groups (p > 0.05). Details related to these tests and their graphs are presented in the following sections.

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