Description of Individual Course Units
Course Unit CodeCourse Unit TitleType of Course UnitYear of StudySemesterNumber of ECTS Credits
404004402018CHEMOMETRY IIElective483
Level of Course Unit
First Cycle
Objectives of the Course
In the light of Statististical background thought in Chemometry I Course, one can be able to analyse calibration and cluster analyse for multiple data.
Name of Lecturer(s)
Assoc.Prof.Dr. Hasan ERTAŞ
Learning Outcomes
1Set-up multivariate data matrices
2Ability in Principal Component Analysis
3Knowledge on scores and loading matrices
4Finding out eigenvalue of data
5Perform Factor Analysis
6Graphical presentation of Scores and Loadings
7Perform Cluster Analysis
8Perform Univariate and multivariate calibration
9Perform the calculation through Principal Component methods and Partial Least Square
10Cross Validation and Test sets for PCA and PLS
Mode of Delivery
Face to Face
Prerequisites and co-requisities
Chemometry I course
Recommended Optional Programme Components
None
Course Contents
The course contain calibration types and clustering / grouping equipment
Weekly Detailed Course Contents
WeekTheoreticalPracticeLaboratory
1Multivariate data matrices
2Methods for Principal Componenet Analysis (PCA)
3Score and Loading Matrices
4Eigen value
5Factor Analysis
6Standardisation
7Cluster Analysis
8Term Exam
9Grouping with PCA
10Calibration
11Univariate Calibration
12Multiple Linear Regression
13Principal Component Regression
14Partial Least Squares
15Method Validation for PLS1 and PLS2
16Final Exam
Recommended or Required Reading
1. Richard G. Brereton, “Chemometrics Data Analysis for the Laboratory and Chemical Plant”, Wiley 1999 2. Mattihias Otto “Chemometrics Statistics and Computer Application in Analytical Chemistry”, Wiley 1999
Planned Learning Activities and Teaching Methods
Assessment Methods and Criteria
Term (or Year) Learning ActivitiesQuantityWeight
SUM0
End Of Term (or Year) Learning ActivitiesQuantityWeight
SUM0
SUM0
Language of Instruction
English
Work Placement(s)
None
Workload Calculation
ActivitiesNumberTime (hours)Total Work Load (hours)
Midterm Examination122
Final Examination122
Attending Lectures14228
Individual Study for Homework Problems4416
Individual Study for Mid term Examination11515
Individual Study for Final Examination12525
TOTAL WORKLOAD (hours)88
Contribution of Learning Outcomes to Programme Outcomes
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1
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10
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22
LO15                     
LO2             3       3
LO3    3                 
LO45        2            
LO5                4     
LO6                      
LO7       5     3        
LO8                  4   
LO9                      
LO10                      
* Contribution Level : 1 Very low 2 Low 3 Medium 4 High 5 Very High
 
Ege University, Bornova - İzmir / TURKEY • Phone: +90 232 311 10 10 • e-mail: intrec@mail.ege.edu.tr