Geo statistics is a branch of statistics which deals with spatial or spatiotemporal data sets. Geo statistics is originally developed to predict distributions of ore grades for mining operations. Now a days Geo statistics is applied in various disciplines which includes Soil science, Petroleum Ecology, Hydrology, Meteorology, Oceanography, Geochemistry, Geo metallurgy, Geography, Forestry, Environmental control, Hydro geology, Landscape ecology, and Agriculture. Geo statistics is applied in many branches of geography, mainly those which include the spread of diseases, the field of commerce, Military and in the development of well-organized spatial networks. Geo statistical algorithms are included in many places, including geographic information systems (GIS) and the R statistical environment. Geo statistics is intimately related to interpolation methods, but extends far beyond simple interpolation problems. Geo statistical techniques rely on statistical model that is based on random variable theory to model the uncertainty associated with spatial estimation and simulation. A number of simpler interpolation methods/algorithms, such as inverse distance weighting, bi linear interpolation and nearest-neighbor interpolation, were already well known before Geo statistics. Geo statistics goes beyond the interpolation problem by considering the studied phenomenon at unknown locations as a set of correlated random variables. In simple Geo statistics means to apply statistics on problems in the eart sciences.