Statistical Modelling: An International Journal is published by SAGE Publications on behalf of the Statistical Modelling Society. It publishes original and high-quality articles that recognize statistical modelling as the general framework for the application of statistical ideas. Submissions must reflect important developments, extensions, and applications in statistical modelling   In straightforward terms, statistical modeling is a rearranged, scientifically formalized approach to inexact reality (for example what produces your information) and alternatively to make forecasts from this estimation. The statistical model is the scientific condition that is utilized Here is an essential model. Assume you need to report the heaviness of an assortment of potatoes. We will consider a hard and a simple method to do it. The most difficult way is going through years estimating the heaviness of each and every potato of this assortment on the planet, and announcing your information in an unending Excel spreadsheet. The easy way is choosing a 30 potato-wide delegate test of this assortment, figuring its normal and standard deviation and revealing just those two numbers as an estimated depiction of this weight. Speaking to an amount by a normal and a standard deviation is an extremely straightforward type of statistical modeling. Another model is endeavoring to speak to the tallness of plants as per soil water content by a straight line portrayed by a slant and a capture drawn after an examination on an example of plants submitted to a developing soil dampness. This specific model is called basic straight relapse.