| Course Unit Title | Course Unit Code | Type of Course Unit | Level of Course Unit | Year of Study | Semester | ECTS Credits |
|---|---|---|---|---|---|---|
| Statistics In Chemistry | KIM441 | Elective | Bachelor's degree | 4 | Fall | 3 |
Name of Lecturer(s)
Prof. Dr. Ümüt AY
Prof. Dr. Deniz BİNGÖL
Associate Prof. Dr. Seda KARAYÜNLÜ BOZBAŞ
Learning Outcomes of the Course Unit
1) Improves basic statistical knowledge
2) Examines errors and error types in chemical analysis
3) Conducts analysis about population and sampling
4) Learning the significance test applications.
5) Evaluates variance analysis
Program Competencies-Learning Outcomes Relation
| Program Competencies | |||||||||||||
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | ||
| Learning Outcomes | |||||||||||||
| 1 | High | High | High | Middle | High | High | Middle | Middle | Middle | Middle | High | Middle | |
| 2 | High | High | High | Middle | High | High | Middle | Middle | Middle | Middle | High | Low | |
| 3 | High | High | High | Middle | High | High | Middle | Middle | Middle | Middle | High | Middle | |
| 4 | High | High | High | Low | High | High | Middle | Middle | Middle | Middle | High | Low | |
| 5 | High | High | High | Middle | High | High | Middle | Middle | Middle | Middle | High | Middle | |
Mode of Delivery
Face to Face
Prerequisites and Co-Requisites
None
Recommended Optional Programme Components
Analytical Chemistry
Course Contents
Basic statistical information, Steps of a chemical analysis, Errors in chemical analyses and error types, Statistics of repeated measurements, Population and sampling, Confidence interval and confidence limits, Significance test, Comparison of two methods, Comparison of two experimental average, Comparison of two sample variance, Extracting excess of deviating values, Variance analysis, Determination of specified limit, Method validation parameters.
Weekly Schedule
1) Importance of statistics in chemistry2) Statistical analysis of experimental data
3) Statistical methods for normal distribution
4) Method validation
5) Evaluation of measurements and results
6) The analysis of variance
7) One-way and two-way analysis of variance
8) Midterm exam
9) Calibration methods: regression and correlation coefficient
10) Calibration graphs in instrumental analysis
11) Standard addition methods
12) Experimental design and optimization
13) Latin squares experiment
14) The quality of analytical measurements
15) Application of analytical data
16) Final exam
Recommended or Required Reading
1- J.N. Miller, J.C. Miller, “Statistics and Chemometrics for Analytical Chemistry”, 05
Edition, Ellis Horwood, 1993.
2- D. Harvet, “Modern Analytical Chemistry”, DePauw University, 2000.
3- D.Brynn Hibbert, J.Justin Gooding, “Data Analysis for Chemistry”, An
Introductory Guide for Students and Laboratory Scientists, Oxford University Pres,
2006.
Planned Learning Activities and Teaching Methods
1) Lecture
2) Question-Answer
3) Discussion
4) Drill and Practice
5) Group Study
6) Brain Storming
7) Lab / Workshop
8) Self Study
9) Problem Solving
Assessment Methods and Criteria
Contribution of Midterm Examination to Course Grade |
40% |
|---|---|
Contribution of Final Examination to Course Grade |
60% |
Total |
100% |
Language of Instruction
Turkish
Work Placement(s)
Not Required