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.