Mutivariate Data Analysis with Aspen Unscrambler

Course Overview

 

·         Gain an understanding of the essential principles of multivariate analysis whilst understanding the primary navigation and handling of data of Aspen Unscrambler.

·         This course teaches the Principle Component Analysis, Regression, and essential sampling and validation techniques to evaluate your data.

·         Introduction to Multivariate Analysis (MVA)

·         Principal Component Analysis (PCA)

·         Outlier detection

·         Multivariate regression

·         Prediction using multivariate models

·         Model validation

Audience:

·         Data Analysts with the technical background

·         Quality assurance and quality control managers or personnel

·         Anyone involved in the functional and technical evaluation of the product, or associated aspenONE Solutions

·         Application and system administrators, system integrators

Training Details

  • Course Id:

    MVA101

  • Duration:

    2 day(s)

  • CEUs Awarded:

    1.4

  • Level:

    Introductory

Benefits

·         Offers a more complete examination of the data by looking at all possible factors.

·         Can help companies predict future outcomes, improve efficiency, make decisions about policies and processes, correct errors, and gain new insights.

·         Multivariate analysis often builds on univariate (one variable) analysis and bivariate (two variable) analysis.

Approach

  • The is a two-day comprehensive course
  • Short lecture sessions focused on concepts and terminology 
  • Structured hands-on lab exercises that promote lasting learning experiences

· 

Subsequent Courses

·         MVA901

·         MVA902

Agenda

·         Introduction to Multivariate Analysis

·         Data import and handling

·         Diagnostics and Plotting

·         Principal Component Analysis

·         Outlier Detection

·         Regression Modelling

·         Validation in Multivariate Analysis

·         Preprocessing

·         Conclusion: How to be a good data Analyst

·         Extra Slides

·         Workshop #1: Data import and visualization (Water)

·         Workshop #2: Introduction to Principal Component Analysis (PCA) (McDonalds)

·         Workshop #3: Interpreting PCA (Peas)

·         Workshop #4: Outlier detection with PCA (City Temperatures)

·         Workshop #5: Introduction to Partial Least Squares Regression (PLSR) (Peas)

·         Workshop #6: Outlier detection with PLSR (EPA)

·         Workshop #7: Multivariate calibration and prediction (Alcohol)

·         Workshop #8: Variable selection with PLSR (Paper)

Register for a Class

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Aspen Technology, Inc. awards Continuing Education Units (CEUs) for training classes conducted by our organization. One CEU is granted for every 10 hours of class participation.