📄 Abstract
<p>Computing the growth of any entity over a time period is important for understanding the past behaviour and for future planning. ‘Compound growth rate’ is one of the frequently used methods for calculating the growth rate models. Among the statistical study was carried out on different growth models<em> viz.,</em> Linear, Quadratic, Cubic, Exponential, Compound, Logarithmic, Inverse, Power, Growth and S-Curve models to project the area, production and productivity cotton crop in India for 1951- 2013. The study revealed that through all models exhibited significant; the cubic model is the best fitted, for its highest adjusted<img height="14" src="file:///C:UsersAntoAppDataLocalTempmsohtmlclip1 1clip_image002.png" width="14" /> on increasing future projection trends with respect to area, production and productivity of cotton in India.</p> <p><strong>KEYWORDS</strong>:<em> Regression growth models; adjusted<img height="14" src="file:///C:UsersAntoAppDataLocalTempmsohtmlclip1 1clip_image002.png" width="14" />; area; production; productivity; cotton.</em></p>
📚 How to Cite:
M. Sundar Rajan , Volume 5 , Issue 10, october 2017, EPRA International Journal of Economic and Business Review(JEBR) ,