Data Analysis (InVision)
Discoverant integrates a powerful investigational and statistical environment for end users integrated with a built-in data access and contextualization technology to provide self-service, real-time, on-demand data access to, and conditioning and analysis of manufacturing and process development data.
- Univariate & Multivariate Statistical Analysis
- Principal Component Analysis & Regression
- General Statistics
- 2D and 3D Plotting
- Statistical Process Control and Alerts
- Stability and Expiration Dating Analysis
- Advanced Profile Analysis
- Multi-Phase Analysis
- Animated 3D Visualizations
Statistical Capabilities
Aegis' Discoverant provides basic and advanced univariate and multivariate statistical tools to help users easily access and analyze everyday process data. For example, users can use Two-Sample t-tests to compare the average of two groups to find out if they are significantly different.
Statistical Examples:
Principal Component Analysis (PCA)
Principal Component Analysis (PCA) can be used to transform a large data set with a large number of correlated variables into a smaller set of uncorrelated variables. These variables can be used in other types of analyses within Discoverant and for further analysis outside of Discoverant.