# Monoplot

A monoplot plots information on the observations or the variables in a multidimensional dataset.

A monoplot can only represent either of the following characteristics - distance between observations, or relationships between variables. In contrast, a joint biplot can represent both characteristics.

A 2-dimensional monoplot represents the information contained in two of the principal components. It is an approximation of the original multidimensional space.

The correlation monoplot plots vectors pointing away from the origin to represent the original variables. The angle between the vectors is an approximation of the correlation between the variables. A small angle indicates the variables are positively correlated, an angle of 90 degrees indicates the variables are not correlated, and an angle close to 180 degrees indicates the variables are negatively correlated. The length of the line and its closeness to the circle indicate how well the plot represents the variable. It is, therefore, unwise to make inferences about relationships involving variables with poor representation.

The covariance monoplot plots vectors pointing away from the origin to represent the original variables. The length of the line represents the variance of the variable, and the inner product between the vectors represents the covariance.

**Available in Analyse-it Editions**

Standard edition

Method Validation edition

Quality Control & Improvement edition

Ultimate edition

- What is Analyse-it?
- Administrator's Guide
- User's Guide
- Statistical Reference Guide
- Distribution
- Compare groups
- Compare pairs
- Contingency tables
- Correlation and association
- Principal component analysis (PCA)
- Principal components
- Scree plot
- Calculating principal components
- Biplot
- Monoplot
- Creating a biplot
- Creating a correlation monoplot
- Factor analysis (FA)
- Item reliability
- Fit model
- Method comparison
- Measurement systems analysis (MSA)
- Reference interval
- Diagnostic performance
- Control charts
- Process capability
- Pareto analysis
- Study Designs
- Bibliography

Version 5.40

Published 29-Jul-2019