{"id":7997,"date":"2025-04-03T11:35:00","date_gmt":"2025-04-03T14:35:00","guid":{"rendered":"https:\/\/cursos.ufrrj.br\/posgraduacao\/ppgq\/?page_id=7997"},"modified":"2025-04-03T11:35:13","modified_gmt":"2025-04-03T14:35:13","slug":"ic-1332h-special-topics-in-chemistry-applied-chemometrics","status":"publish","type":"page","link":"https:\/\/cursos.ufrrj.br\/posgraduacao\/ppgq\/en\/ic-1332h-special-topics-in-chemistry-applied-chemometrics\/","title":{"rendered":"IC-1332h -Special Topics in Chemistry: Applied Chemometrics"},"content":{"rendered":"\n

2 credit corresponds to 15h\/class<\/strong><\/p>\n\n\n

OBJECTIVES OF THE DISCIPLINE:<\/strong>
Familiarize students with the basic concepts and techniques of multivariate analysis. Give an overview of multivariate data analysis methods and show their applications to different chemical problems.<\/p>\n

SUMMARY:<\/strong>
1. Introduction
2. Multivariate Data
3. Principal Component Analysis
4. Calibration and Classification
5. Cluster Analysis<\/p>\n

ANALYTICAL PROGRAM:<\/strong>
1. Introduction
the. Definition and History
b. Examples<\/p>\n

2. Multivariate Data
the. Definitions
b. Processing
w. Covariance and Correlation
d. Distances and Similarities
and. Identification of Outliers
f. Latent Linear Variables<\/p>\n

3. Principal Component Analysis
the. Concepts
b. Algorithms
w. Assessment and Diagnostics
d. Complementary Methods<\/p>\n

and. Examples<\/p>\n

4. Calibration
the. Concepts
b. Regression Models
w. Simple Linear Regression
d. Robust Regression
and. Variable Selection
f. Regression by Principal Components
g. Partial Least Squares Regression
h. Examples<\/p>\n

5. Classification
the. Concepts
b. Linear Classification Methods
w. Kernel and Prototype-based Methods
d. Classification Trees
and. Neural Networks
f. Support Vector Machine
g. Assessment
h. Examples<\/p>\n

6. Cluster Analysis
the. Concepts
b. Distance and Similarity Measures
w. Partitioning Methods
d. Hierarchical Cluster Analysis Methods
and. Fuzzy Clustering
f. Model-Based Groupings
g. Trend Validation and Measurements
h. Examples<\/p>\n

Bibliography<\/strong>
1. Introduction to multivariate statistical analysis in chemometrics \/ Kurt Varmuza and Peter Filzmoser, 2009.
2. Applied Multivariate Statistical Analysis \/ Wolfgang H\u00e4rdle and L\u00e9opold Simar, 2003.
3. Chemometrics – Data Analysis for the Laboratory and Chemical Plant \/ Richard G. Brereton, 2003.<\/p>","protected":false},"excerpt":{"rendered":"

2 credit corresponds to 15h\/class OBJECTIVES OF THE DISCIPLINE:Familiarize students with the basic concepts and techniques of multivariate analysis. 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