Multivariate analysis is a set of techniques used for analysis of data that contain more than one variable. There is always more than one side to the problem you are trying to solve. It’s the same in your data.
30% Product quality increase
25% Waste reduction
20% Energy reduction
Unlocking the data potential
Multivariate analysis is a set of statistical and machine learning techniques used for analysis of data that contain more than one variable
The digital economy generates fast growing masses of data from old and new industrial infrastructures. This data holds the potential to be the most valuable asset for your company. Sure, there is value in aggregating and visualising the data, but there is always more than one side to the problem you are trying to solve. It’s the same in your data. The only way to solve the complex problems and realise the full potential is by analysing all variables and dimensions of the data using multivariate analysis. Only then will you get insights that reflects your industrial reality – and how to optimise it.
Multivariate analysis refers to any statistical or machine learning technique used to analyze more complex sets of data. There are more than 20 different methods to perform multivariate analysis and which method is best depends on the type of data and what you are trying to solve. Essentially you build models that reflects an actual product or process and optimise it using different methods.
Multivariate analysis is typically used for:
- Quality control and quality assurance
- Process optimization and process control
- Research and development
- Consumer and market research
How multivariate methods are used
- Obtain a summary or an overview of a table. This analysis is often called Principal Components Analysis or Factor Analysis. In the overview, it is possible to identify the dominant patterns in the data, such as groups, outliers, trends, and so on. The patterns are displayed as two plots
- Analyze groups in the table, how these groups differ, and to which group individual table rows belong. This type of analysis is called Classification and Discriminant Analysis
- Find relationships between columns in data tables, for instance relationships between process operation conditions and product quality. The objective is to use one set of variables (columns) to predict another, for the purpose of optimization, and to find out which columns are important in the relationship. The corresponding analysis is called Multiple Regression Analysis or Partial Least Squares (PLS), depending on the size of the data table
The multivariate difference
Multivariate analysis provides a more accurate view of the behavior between variables that are highly correlated, and can detect potential problems in a product or process.
Follow the red-dots: Looking at the variables individually there are no apparent issue but combining them in a multivariate view immediately reveals an issue
Many decisions are based on univariate analysis, but only multivariate analysis reveals relationships that help you detect problems that are not obvious by looking at the variables individually.
Examples of multivariate analysis in action
For decades process and product quality issues have been solved with our world-leading multivariate analysis tool, Unscrambler.
Using multivariate analysis Nidar is able to resolve product quality problems and optimise their manufacturing processes from better process understanding
Multivariate analysis helps SAB Miller create leading brands and get greater value from their manufacturing and market research data
HarvestLab® from ZEISS and John Deere uses multivariate analysis for on-the-go measuring of moisture, dry matter, protein, starch, fiber, neutral detergent fiber, acid detergent fiber, and sugar
Try multivariate analysis in action – download free trial!
The Unscrambler® is the most easy to use all-in-one tool with powerful multivariate analysis, interactive graphics and visualizations. It is the preferred tool for 25,000 data analysts, researchers and engineers who need to analyze data quickly, easily and accurately.
Get hands-on experience with multivariate analysis on one of our upcoming courses
Maximize your analytical skills and accelerate your organisations success using multivariate analysis with our flexible training options to suit different learning preferences and skill levels.
New book: An introduction to Multivariate Analysis
All updated 6th edition of the best selling book on chemometrics and multivariate techniques, covering PLS, PCA, TOS, DoE and much more.