Statistical analysis methods include descriptive statistics, inferential/predictive statistics and kriging.

Descriptive statistics: Used to describe what a large amount of data shows, in a simple way. Numerical descriptors include the mean and standard deviation for continuous data, and frequency and percentage for categorical data. Graphical descriptors include the histogram, scatter graph and box plot. Descriptive statistics are generally presented along with more formal analyses, to give an overall sense of the data being analysed.

Inferential / Predictive statistics: The formation of conclusions about almost any parameter from a random sample taken from a larger population. These inferences may take the form of answers to yes/no questions (hypothesis testing), estimates of numerical characteristics (estimation), descriptions of association (correlation), or modelling of relationships (regression), extrapolation and interpolation.

Descriptive statistics and inferential statistics together comprise applied statistics.

Kriging: A form of statistical modelling, commonly used in geostatistics, to predict unknown values from a known set of sample points to a continuous surface. For example, it can be used to interpolate the elevation of a landscape at an unobserved location, from observations of its value at nearby locations.

Related methods include: Geo-referencing and projection, Overlaying and Photogrammetry.