Statistical Diagrams in Micromine. Definitions and Functionalities
Statistical diagrams are a powerful tool for analysing and processing geological data during geological exploration and resource estimation. Visualisation via charts allows to better understand and interpret complex data, identify relationships and trends, simplifying decisions. Micromine provides extensive capabilities for comprehensive statistical processing of geological databases with a wide range of statistical charts, plots and graphs.
Micromine Origin & Beyond has a special Statistics toolbar, which consists of 6 main sections and contains all statistical tools, including diagrams:
 Exploratory Data Analysis: Histogram, Histogram (Multivariate), Box and Whisker, Scattergram, QQ Plot.
 Transformation: Gaussian Anamorphosis, Change of Support, Cell Declustering, PCA (Principal Component Analysis).
 Variography: Variogram Map, Variogram, Omnidirectional Variogram, Cross Validation.
 Analysis: Top Cut, Boundary Analysis, Swath Plot, Search Neighbourhood, Quantitative Kriging Neighbourhood Analysis (QKNA), Grade Tonnage Curve.
 Charts: Multipurpose Chart, Ternary Diagram, Gantt Chart, Spider Graph.
 Assay Quality Control: Continuous Sampling, Shewhart Control Chart, Cumulative Sum (CUSUM) Chart.
The following overview of all chart, graph and plot types with a description of functionality and purpose can help you to navigate the variety of statistical tools provided by Micromine and successfully use them in daily operations. The geological applications of each diagram type are not exhaustive, but provide only some examples of such applications in different geological areas.
Diagram  Description of Functionality  Geological Application 
Histogram 
Histogram is a graphical illustration of the distribution of numerical data. Data is divided into a series of intervals (bins), each indicating a range of values. Bins are represented as bars, the height of which corresponds to the number of observations or the frequency of values in each interval. 

Histogram (Multivariate) 
Multivariate (Comparative) Histogram is a statistical tool used to visualise the joint distribution of multiple variables or multiple data sets simultaneously. Unlike univariate histograms, multivariate histograms allows to analyse multiple variables and relationships. 

Box and Whisker 
Box and Whisker Plot (or Box Plot) graphically describe the spread and means of one or more distributions of numerical data. These plots provide a general summary of the data distribution, highlighting essential statistical features that are important for geological analysis. 

Scattergram 
Scattergram (scatter plot, scatter graph or scatter chart) is a type of graph used to display the relationship between two variables. The position of each point on the graph corresponds to the values of the two variables for that data point.
It is used in correlation analysis to establish relationships between different geological factors or variables. The width of the scatter of the points can indicate the closeness of the population’s relationship. 

QQ Plot 
Q–Q (quantile–quantile ) Plot is a probability plot, a graphical method for comparing two probability distributions by plotting their quantiles against each other. It is often used to assess the fit of a data set to a theoretical distribution, such as the standard normal distribution.
If the points lie on or near the straight line, the sample data is consistent with the theoretical distribution. Deviations from the line suggest discrepancies between the sample and theoretical distributions. 

Gaussian Anamorphosis 
Gaussian Anamorphosis is a geostatistical tool used to process data that does not follow a normal distribution. This transformation allows the use of geostatistical methods that require a normal distribution. 

Change of Support 
Change of Support is a concept used to analyze and compare data collected at different scales or levels of detail (e.g. drill hole composites and mining blocks). So, the basis change model predicts how the grade distribution changes with volume support considering only data and statistics of the composited drill hole data. 

Cell Declustering 
Cell Declustering (or Spatial Declustering) is a geostatistical technique that provides a more representative statistical representation by weighting of data points based on their spatial distribution. Declustering is used to solve the problem of spatially clustered data points that can introduce bias into statistical analysis. 

Principal Component Analysis 
Principal Component Analysis (PCA) is a factor analysis method in statistics for reducing the dimensionality of multivariate data sets by transforming the original variables into a new set of uncorrelated variables called principal components. 

Variogram Map 
Variogram Map is a graphical tool for analysing and visualising the spatial autocorrelation of geological properties and parameters in different directions using polar coordinates. It is essentially a matrix or grid where each cell represents the semivariations between pairs of data points, which helps to identify the anisotropy and directionality of spatial data. 

Variogram

Variogram is a fundamental tool in geostatistics used to quantify spatial continuity and variability in a set of spatially distributed data. It measures how the similarity between data points changes with distance. The variogram configuration is determined by basic parameters such as range, nugget effect, and threshold. 

Omnidirectional Variogram 
Omnidirectional Variogram is a type of variogram that measures spatial autocorrelation without considering the direction of the pairs of points. It treats all distances (lags) between data points equally, regardless of their direction, and provides an average measure of spatial variability over all directions. 

Cross Validation 
Cross Validation (Rotation Estimation or OutofSample Testing) is a statistical method used to evaluate the precision and reliability of a predictive model. Some data points are temporarily removed from the sample, their values are estimated using the remaining data points, and the estimated values are compared with the actual values. 

Top Cut 
Top Cutting, also known as Capping, is the practice of limiting the maximum values of samples to manage the impact of extremely high grades on resource estimation. This avoids the disproportionate affect of extremely high values on the average grade and resulting resources.
The following methods and diagrams are used for Top Cutting: Decile Analysis, Histogram, Cumulative Frequency, Probability Plot, Mean vs Cut, CV vs Top Cut, Relative Nugget vs Top Cut 

Boundary Analysis 
Boundary (Contact) Analysis Diagram is a tool for delineating and visualizing the boundaries between different geological units or zones. This type of diagram helps to analyse changes in geological properties at these boundaries and determine the contact nature (hard or soft).
The Boundary Analysis works using spatial statistics of the investigated domains with equal binning of data from the contact (zero distance) at regular distance increments until the maximum distance is reached or no data is available. 

Swath Plot 
Swath Plot is a graphical display of a value or parameter distribution from a series of bands, or swaths, generated in several directions. 

Search Neighbourhood 
Search Neighbourhood checks the optimality of the search ellipsoid parameters, which defines the spatial region around a point of interest from which data is used to estimate the value at that point. 

Quantitative Kriging Neighbourhood Analysis 
Quantitative Kriging Neighborhood Analysis (QKNA) is a geostatistical method for assessing and optimising kriging search parameters (the size and shape of the search area, as well as the number of data points). QKNA involves kriging variance, kriging efficiency, slope of regression, percent negative weights, etc. 

Grade Tonnage Curve 
GradeTonnage Curve (GTC) is a graphical representation of the relationship between the tonnage of ore or mineral and its average grade. GTC is one of the more useful means of summarizing mineral resource estimation.
Generally, three curves are involved: (1) graph of tonnage above cutoff grade versus cutoff grade, (2) average grade of tonnage above cutoff versus cutoff grade and (3) quantity of metal versus cutoff grade. 

Multipurpose Chart 
Multipurpose Chart is a versatile graphical tool designed to display various types of data and relationships in a single chart. These charts can combine multiple data visualization techniques, such as bar charts, line graphs, scatter plots, and more, to provide a comprehensive view of the information. Multiple axes can be used to compare different data sets with different scales. 

Ternary Diagram 
Ternary Diagram (Triangle Plot) is a graphical representation used to display the proportions of three variables that sum to a constant value, often 100%. It consists of three axes, each representing one of the components in the threecomponent system. The position of each point is determined by the ratio (percentage) of the three components. 

Gantt Chart 
Gantt Chart is a graphical representation of activity against time that is used to plan tasks and monitor progress. The timelines are horizontal bars and form a bar chart. 

Spider Graph 
A Spider (Radar or Star) Graph is a type of data visualization used to display multiple variables on a single chart, each represented by a separate axis radiating from a central point. 

Continuous Sampling 
Histogram with theoretical probability density function is used for graphical and statistical comparison of a sampling against a theoretical distribution. 

Shewhart Control Chart 
Shewhart Control Chart (Processbehavior Chart) is a graph of changes in process parameters by time, which is used to provide statistical control of process stability.
The centre line (reference or mean value) and control levels (based on the standard deviation) help to check the stability of the process and identify potential anomalies. 

Cumulative Sum (CUSUM) Chart 
A Cumulative Sum (CUSUM) Chart is a graph aimed at monitoring the variability of a continuous variable based on the cumulative value of deviations from a reference (or average).
This chart is an effective alternative to the Shewhart Chart but is more sensitive to detecting small deviations from the mean. 

A statistical chart allows you to interactively operate with source data, such as a table of laboratory results or a Vizex (Map). For example, selecting a histogram column or another part of the data in a diagram, we can see it highlighted in the corresponding source file or in Vizex. It helps you understand data distribution patterns and trends more deeply.
The wide range of statistical tools offered by Micromine Origin & Beyong allows you to better understand your exploration or mining project. Analysing and interpreting geological data using modern statistical charts and plots, you can make more informed decisions for targeting geological exploration and mineral mining.
For more details about specific examples of statistical diagrams for geological tasks, please follow the corresponding material “Statistical diagrams in Micromine. Examples of application“.