COURSE UNIT TITLE

: CHEMOMETRICS

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
KIM 5035 CHEMOMETRICS ELECTIVE 3 0 0 7

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

Offered to

Chemistry
Chemistry
Chemistry

Course Objective

In this course, formal methods for the selection and optimization of analytical methods and procedures and for the interpretation of data will be disscussed and explained in details.

Learning Outcomes of the Course Unit

1   To be able to learn how the experimental data are evaluated statistically.
2   To be able to explain methods ad algorithms for the analysis and modeling of experimental data.
3   To be able to analyse analytical problems, carry out planning and design of experiments, present of the results.
4   To be able to propose suitable statistical methods for optimization of analytical procedure, compare F-test, paired t- test, analysis of variance.
5   To be able to explain formal methods for the selection and optimization of analytical methods and procedures and discuss the interpretation of data.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Analytical problems, types of error, planning and design of experiments, mean, standard deviation, distribution of errors, confidence limit of mean, presentation of results, propagation of errors
2 Comparison of means, paired t-test, F-test, outliers, analysis of variance, chi-squared test
3 Calibration, analysis of residuals, multivariate lineer regression, regression lines for comparing analytical methods
4 Weighted regression lines, curve fitting, detection limit
5 Sign test, wald-wolfowitz run test, wilcoxon rank sum test and related methods, non-parametric test on more than two samples, rank correlation, kolmogorov test for goodness of fit
6 Multivariate distribution, pattern,classes and distances
7 Pattern recognition, factorial design and optimization I
8 Pattern recognition, factorial design and optimization II
9 Definition of principal component analysis, procedure for principal component analysis, factor analysis
10 Determination of factors, rotation of factors, other display methods
11 Problem of separating groups, discrimination using Mahalanobis distances, canonical discriminant functions
12 Stepwise discriminant function analysis, assigning of ungrouped individuals to groups
13 Use of cluster analysis, types of cluster analysis, hierarchic methods
14 Problems of cluster analysis, principal component analysis wşth cluster analysis

Recomended or Required Reading

J. C. Miller, J. N. Miller, Statistics for Analytical Chemistry , Ellis Horwood PTR, Prentice Hall, London, N.Y., 3rd edition, 1993.
B. F. J. Manly, Multivariate Statistical Methods , Chapman and Hall, London, N.Y., 1989
D. L. Massart, B. G. M. Vandeginste, S. N. Deming, Y. Michotte, L. Kaufman, Chemometrics , Elsevier Science Publishers, 1988.

Planned Learning Activities and Teaching Methods

Room lessons, student centered activities, exercises using computer.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 FIN FINAL EXAM
3 FCG FINAL COURSE GRADE MTE * 0.40 + FIN * 0.60
4 RST RESIT
5 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.40 + RST * 0.60


Further Notes About Assessment Methods

None

Assessment Criteria

Assessment of the students will be done by using mid-term exam and final examination as can be seen from above gradings.

Language of Instruction

English

Course Policies and Rules

Attendance to at least 70% for the lectures is an essential requirement of this course and is the responsibility of the student. It is necessary that attendance to the lecture and homework delivery must be on time. Any unethical behavior that occurs either in presentations or in exams will be dealt with as outlined in school policy. You can find the undergraduate policy at http://web.deu.edu.tr/fen

Contact Details for the Lecturer(s)

DEU Science Faculty Chemistry Deparment
e-mail: melek.merdivan@deu.edu.tr
Tel: 0 232 3018693

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparation for Mid-term Exam 1 30 30
Preparation before/after weekly lectures 14 5 70
Preparation for Final Exam 1 35 35
Mix-term 1 3 3
Final 1 3 3
TOTAL WORKLOAD (hours) 183

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11
LO.13
LO.23
LO.34
LO.43
LO.53

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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