The budget allocation is calculated based on the correlation of the various significant factors with IMR. If a factor has high correlation with IMR, then that factor has to be allocated more budget than others. The method also takes into … Continued
This data story analyses various factors from multiple sources that are highly correlated with the Secondary Dropout Rate at the taluk level and uses predictive analysis to estimate the impact of changes in each factor on districts and taluks. The … Continued
You can select the variable for which you want to see correlation with secondary dropout rate, from the dropdown menu. If p-value for a variable is less than 0.05, then that variable has significant correlation with secondary dropout rate. Out … Continued
In the below dashboard, we can see the crop diversity of districts as well as taluks. Crop diversity is a measure of the capability of a region to grow diverse crops. If a region can grow many diverse crops with … Continued
You can select the variable for which you want to see correlation with dropout rate, from the dropdown menu. If p-value for a variable is less than 0.05, then that variable has significant correlation with dropout rate.
You can select the variable for which you want to see correlation with primary pass ratio, from the dropdown menu. If p-value for a variable is less than 0.05, then that variable has significant correlation with primary pass ratio.