Business

The Unscrambler combines statistical analysis techniques and multivariate mapping for easier data interpretation. This means users can effortlessly perform powerful statistical analysis while easily communicating results to colleagues.



Multivariate Curve Resolution (MCR): Resolves mixtures by determining the number of constituents, their spectral profiles and their estimated concentrations

Descriptive statistics (Mean, Standard Deviation, Box-Plot, skewness, kurtosis, correlation matrix)

Principal Component Analysis (PCA)

Regression (MLR, PCR, PLS-R, 3-way PLS-R)

Prediction from PCR, PLS-R and 3-way PLSR models

Classification (SIMCA, PLS-DA)

ANOVA and Response Surface ANOVA

Validation options: Leverage Correction, Cross-Validation (freely choose number of samples per segment), Test Set

Variable Scaling options: Scaling is free on each variable. Suggested options: Auto-scaling, Constant, Passify

Interaction and Square terms can be included in all models

Smart Tools for Analysis



Analytical tools required to decipher data and create innovative solutions.

Automatic detection of significant X-variables in PCR and PLS-R

Model Stability in PCA, PCR and PLS-R

Automatic outlier detection in PCA, MLR, PCR, PLS-R and Prediction

Message list of recommendations in MCR modeling



Interactive analysis:

Mark samples and/or variables on plots

Recalculate With or Without Marked samples or variables

Recalculate With Passified Marked or Unmarked variables

Extract Data from Marked or Unmarked

Automatic Pretreatments in Prediction and Classification

Tutorial exercises guiding you through the use of all The Unscrambler modeling techniques in application examples



Design of Experiments

Design Wizard: Takes you through the stages of building a design

Fractional and Full Factorial designs

Plackett-Burman designs

Box Behnken designs

Mixture designs (Simplex-Lattice, Axial, Simplex-Centroid)

Download Links:

The Unscrambler – Multivariate Data Analysis Software 9.5