Description of Individual Course Units
Course Unit CodeCourse Unit TitleType of Course UnitYear of StudySemesterNumber of ECTS Credits
KİM003CHEMOMTRYElective233
Level of Course Unit
First Cycle
Objectives of the Course
The aim of this course is to provide an introduction to the knowledge and applied chemometric approach to data analysis in Analytical Chemistry. The use of data analysis programs to solve real problems will be emphasized.
Name of Lecturer(s)
Doç.Dr.Hasan Ertaş
Learning Outcomes
1 Ability to communicate about general characteristics of statistical information
2An ability to evaluate statistical data
3Ability to follow scientific studies and to interpret information about chemometry
4Ability to make an experimental design in optimization studies
5Ability to create Calibration Curve and calculate errors
Mode of Delivery
Face to Face
Prerequisites and co-requisities
-
Recommended Optional Programme Components
-
Course Contents
1- Basic Concepts: General definition of chemometry, relationship with analytical chemistry, significant figures and statistical parameters 2- Probability and distribution types: Normal distribution, Poisson and Binomial distributions 3- Types of Error: Differences of errors, partial validation (reproducibility, reproducibility, precision, reality, accuracy) 4- Null Hypothesis: Confidence interval, t-test, F test 5- Q test, (Fisher) Grubbs Test and Measurement Uncertainty 6- Least Squares Method: Drawing a Calibration Curve: Calibration Curve sources of error and calculation 7- Single and Double Factor ANOVA 8- Matrix operations 9- Experimental Design: Partial and full factorial design 10- Placket Burman or Taguchi Design 11- Central Composite Design
Weekly Detailed Course Contents
WeekTheoreticalPracticeLaboratory
1Definition of chemometry, significant figures, units and statistical parameters
2Probability and distributions, types of errors, accuracy, accuracy, partial validation of reality
3Null hypothesis, confidence interval, t test, F test
4Q test, Grubbs test, measurement uncertainty
5Least squares method, drawing a calibration graph
6Sources of error of calibration chart
7Single Factor ANOVA
8Midterm Exam
9Two-factor ANOVA
10Matrix operations
11Denel Design
12 Partial and Full factorial design
13Plackett-Burman or Taguchi design
14 Central Composite Design
15Central Composite Design
16Final Exam
Recommended or Required Reading
1. J.C.Miller, J.N.Miller,”Statisticsfor Analytical Chemistry”Ellis Horwood PTR Prentice Hall,1993, 2. K.R.Beebe, R.J.Pell, M.B. Seasholtz,”Chemometrics:A Practical Guide”,J.Wiley&Sons, 1998 3. J.N.Miller&J.C.Miller Fifth Edition Pearson, Prentice Hall, 2005, Statistics and Chemometrics for Analytical Chemistrty YARDIMCI KİTAPLAR: 1. Applied Statistics and Probability for Engineers, Douglas C. Montgomery, George C.Runger, John Wiley Fifth Edition 2011. 2. Stephen LR Ellison, Vicki J.Barwick and Trevor J. Duguid Farrant 2nd Edition RSC Publishing 2009
Planned Learning Activities and Teaching Methods
Assessment Methods and Criteria
Term (or Year) Learning ActivitiesQuantityWeight
Midterm Examination1100
SUM100
End Of Term (or Year) Learning ActivitiesQuantityWeight
Final Examination1100
SUM100
Term (or Year) Learning Activities40
End Of Term (or Year) Learning Activities60
SUM100
Language of Instruction
Turkish
Work Placement(s)
-
Workload Calculation
ActivitiesNumberTime (hours)Total Work Load (hours)
TOTAL WORKLOAD (hours)0
Contribution of Learning Outcomes to Programme Outcomes
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* 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