Instructor Led Experimental Design Training Classes

Multivariate Data Analysis MVA and Design of Experiments DoE Level-1 Bangalore July 21-23 2008 Multivariate Analysis Level - 1 -------------------------------- * The world is multivariate Introduction to multivariate data modelling * When are multivariate methods useful? * Principal Component Analysis (PCA) * Multivariate regression: => MLR- Multi Linear Regression => PCR- Principal Component Regression => PLS- Partial Least Squares * Relevant data collection * Multivariate more...

Experimental Design DoE The Design of Experiment training will provide participants with an overview of Experimental Design, its importance in multivariate statistics and an introduction to classical experimental strategies. The course will assume no previous statistical or DOE experience, but will accommodate advanced topics for seasoned practitioners as well. more...

Experimental Design (DoE) ...shop that will teach participants to use The Unscrambler Experimental Design suite to design and conduct experiments. The course will provide participants with an overview of Experimental Design, its importance in Multivariate Statistics and an introduction to classical experimental strategies. Participants are encouraged to bring their own data for analysis, applications development and group more...

Statistics Training : Multivariate Data Analysis CAMO offers comprehensive training courses and applications development workshops in Multivariate Data Analysis I and II Introduction to Multivariate Statistical Analysis with Chemometrics and Spectroscopy, Multivariate Analysis for NIR Spectroscopy, Near-Infrared Technology- Getting the most out of Light Multivariate Statistical Analysis for Process Analytical Technology (PAT) more...

Design of Experiments : Statistics : Advanced Training Course ...Experimental Design Statistic Apart from an Introduction to the Design of Experiments, this training session focuses on the design and the analysis of highly complex experimental designs. These designs are used to account for different sources of experimental constraints such as material heterogeneity, physical constraints, repeated measures , etc. Their design and analysis will be more...

Design of Experiments for Injection Molding Injection molders must be able to quickly identify the optimal setpoints for molding process variables in order to meet customer performance requirements for dimensions and part appearance. The complexity of this task grows exponentially as the number of customer critical characteristics increases. Trial and error approaches are highly inefficient in these situations. Simple experimental design more...

Design of Experiments - Public Seminar ...approaches of DOE. Efficient and effective application of experimental design require a blending of key skills. Knowledge of the relevant technologies, team communication skills, and some simple mathematical tools all come into play (in this session we rely upon the computer to crunch the numbers while we focus on interpretation of key graphics and output tables). The following is what makes more...

Fundamental Tools in Statistics An efficient and effective one-day refresher on the fundamental tools in statistics. This course covers the two main divisions of statistics: descriptive and inferential statistics. First, the course covers descriptive statistics : the different types of variables, variability, distributions and the characterization of distributions through well-known statistics such as the mean and standard more...

Advanced Experimental Designs This course covers the fundamental concepts in statistics in a non-technical and applied way. This session focuses on the design and the analysis of more complex experimental designs than those seen in the Introduction to the Design of Experiments course. These designs are used to account for different sources of experimental constraints such as material heterogeneity, physical constraints, more...

Multivariate Data Analysis Introduction to multivariate data modeling When are multivariate methods useful? Principles and applications of: Principal Component Analysis (PCA) Multivariate regression: Multi Linear Regression (MLR), Principal Component Regression (PCR), Partial Least Squares (PLS) Relevant data collection Multivariate modeling step by step Pretreatment and scaling Detecting and dealing with more...