CHP3MultivariateStatistics

CHP3MultivariateStatistics - Chapter 3 Click to edit Master...

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Click to edit Master subtitle style 4/10/11 Chapter 3 Multivariate Statistics, Calibration, and Quality Control Bell Text

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4/10/11 Multivariate Statistics Application of statistics to data sets with more than one variable Tasks requiring multivariate statistics are: Descriptive Predictive Classification Chemometrics – focuses on analysis of chemical data “exploratory data analysis” (EDA) and modeling
4/10/11 Predictive Modeling & Linear Regression – a common technique used to calibrate instruments: y = mx + b Linear Range Limit of Quantitation (LOQ) Limit of Detection (LOD) Least Squares

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4/10/11 Linear Calibration Curves
4/10/11 Forcing Line Through 0,0

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4/10/11 Correlation Coefficient
4/10/11 Exploratory Data Analysis (EDA) Studies data and identifies relationships and patterns within the data (mostly within large

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4/10/11 Exploratory Data
4/10/11 Exploratory Data

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4/10/11 EDA Correlations
4/10/11 EDA Correlations

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Principle Component Analysis (PCA) When linear relationships exist among variables, PCA finds groups and patterns in data by reducing dimensionality of data In a case where there are 3 variables, 3 principle components exist: Z1 = a11X1 + a12X2 + a13X3 Z2 = a21X1 + a22X2 + a23X3
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This note was uploaded on 04/09/2011 for the course CHEM 4461 taught by Professor Max during the Spring '08 term at Lamar University.

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CHP3MultivariateStatistics - Chapter 3 Click to edit Master...

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