First of all, R-square value is 0.98 (Table 3), whichshows a high significance of the model in determining the relationship among the chosen variables. The high value of R-square caused a highF -value (Table 4), which confirms that the null hypothesis is rejected, which makes the result significant. The value of the significance is more than 0.05, which is used as an overall value that is 5.3 (Table 4). Due to different respondents from different cities in this sample, the significance value shows the chances of difference between populations. Indeed, each farmer’s experience is different. Instead of random sampling, purposive sampling was used to target only farmers. The regression value also indicates that we have discarded the right prediction as a Y-intercept value.
Table 4. ANOVA.