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Information
| Code | MN0017 |
| Name | Statistical Modeling in Material Science |
| Term | 2024-2025 Academic Year |
| Term | Fall |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | İngilizce |
| Level | Doktora Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | |
| Course Instructor |
1 |
Course Goal / Objective
Learning statistical modeling and quality control methods in materials science
Course Content
Introduction to Statistics and Data Analysis. Probability and Mathematical Expectation. Discrete and Continuous Probability Distributions. Sampling Distributions and Data Descriptions. One- and Two-Sample Estimation Problems. One- and Two-Sample Tests of Hypotheses. Simple Linear Regression and Correlation. Multiple Linear Regression and Certain Nonlinear Regression Models. One-Factor Experiments: General. Factorial Experiments (Two or More Factors). 2k Factorial Experiments and Fractions. Nonparametric Statistics. Bayesian Statistics. Statistics Applications in Materials Science.
Course Precondition
To have knowledge on probability.
Resources
1-) Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, Keying Ye, Probability & Statistics for Engineers & Scientists, 9th edition, Prentice Hall, (2012) 2-) Jeffrey P. Simmons, Lawrence F. Drummy, Charles A. Bouman, Marc De Graef, Statistical Methods for Materials Science - The Data Science of Microstructure Characterization, 1st edition, CRC Press, (2019)
Notes
1-) Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, Keying Ye, Probability & Statistics for Engineers & Scientists, 9th edition, Prentice Hall, (2012) 2-) Jeffrey P. Simmons, Lawrence F. Drummy, Charles A. Bouman, Marc De Graef, Statistical Methods for Materials Science - The Data Science of Microstructure Characterization, 1st edition, CRC Press, (2019)
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Calculates statistical parameters with data. |
| LO02 | Learns discrete probability distributions. |
| LO03 | Learns continuos probability distributions. |
| LO04 | Performs hypothesis tests. |
| LO05 | Develops experimental design. |
| LO06 | Creates a statistical model with the data obtained from the experiments. |
| LO07 | Interprets statistical model results. |
| LO08 | Learns regression models. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Based on the qualifications gained during PhD studies, develops and deepens the current and advanced knowledge in the area by unique means of thinking and / or research at mastery level and comes up with original definitions which bring about novelty to the area. | 3 |
| PLO02 | Beceriler - Bilişsel, Uygulamalı | Can effectively use the equipment used in the field. | |
| PLO03 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Selects experimental measurement methods of various physical quantities and uses instruments in accordance with their sensitivity limits. | |
| PLO04 | Yetkinlikler - Alana Özgü Yetkinlik | Interprets experimental and observational results. | 5 |
| PLO05 | Yetkinlikler - Öğrenme Yetkinliği | Can draw conclusions from the information obtained during the preparation for the PhD qualifying exam. | 3 |
| PLO06 | Bilgi - Kuramsal, Olgusal | Can interpret the information acquired about the field orally and in writing. | 5 |
| PLO07 | Bilgi - Kuramsal, Olgusal | Uses mathematical methods related to the field of study. | |
| PLO08 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Have knowledge about the logic, design, conclusion and dissemination of results of scientific research. | 3 |
| PLO09 | Bilgi - Kuramsal, Olgusal | Uses the theoretical and applied knowledge gained in the field of materials and nanotechnology at the level of expertise. | |
| PLO10 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Gains high-level skills in using research methods in studies related to materials science and nanotechnology. | |
| PLO11 | Bilgi - Kuramsal, Olgusal | Develops a scientific method that brings innovation to science. | |
| PLO12 | Yetkinlikler - Alana Özgü Yetkinlik | Makes critical analysis, synthesis and evaluation of new ideas related to the field. | 4 |
| PLO13 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Can carry out independent research on a specific topic related to materials and nanotechnology. | |
| PLO14 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Be able to lead in the execution of interdisciplinary studies. | 5 |
| PLO15 | Yetkinlikler - Öğrenme Yetkinliği | Follows the developments in the her/his field of study and constantly renews herself/himself. | 4 |
| PLO16 | Bilgi - Kuramsal, Olgusal | Calculate the predictions of the theories and compare them with the experimental results. | 4 |
| PLO17 | Yetkinlikler - Öğrenme Yetkinliği | Comprehends the interdisciplinary interaction that the field of study is related to. | 5 |
| PLO18 | Yetkinlikler - Alana Özgü Yetkinlik | He/she shares his/her own ideas and suggestions regarding the problems in the field of study with groups in and outside the field by supporting them with quantitative and qualitative data. | 4 |
| PLO19 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Can develop original solutions for problems in the field. | 3 |
| PLO20 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Can prepare a scientific article and publish scientific articles in international refereed journals. | 4 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Introduction to Statistics and Data Analysis. | Study the relevant chapter of the textbook. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 2 | Probability and Mathematical Expectation. | Study the relevant chapter of the textbook. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 3 | Discrete and Continuous Probability Distributions. | Study the relevant chapter of the textbook. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 4 | Sampling Distributions and Data Descriptions. | Study the relevant chapter of the textbook. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 5 | One- and Two-Sample Estimation Problems. | Study the relevant chapter of the textbook. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 6 | One- and Two-Sample Tests of Hypotheses. | Study the relevant chapter of the textbook. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 7 | Simple Linear Regression and Correlation. | Study the relevant chapter of the textbook. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 8 | Midterm exams | Ölçme Yöntemleri: Yazılı Sınav |
|
| 9 | Multiple Linear Regression and Certain Nonlinear Regression Models. | Study the relevant chapter of the textbook. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 10 | One-Factor Experiments: General. | Study the relevant chapter of the textbook. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 11 | Factorial Experiments (Two or More Factors). | Study the relevant chapter of the textbook. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 12 | 2k Factorial Experiments and Fractions. | Study the relevant chapter of the textbook. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 13 | Nonparametric Statistics. | Study the relevant chapter of the textbook. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 14 | Bayesian Statistics. | Study the relevant chapter of the textbook. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 15 | Statistics Applications in Materials Science. | Study the relevant chapter of the textbook. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 16 | Final exams | Ölçme Yöntemleri: Yazılı Sınav |
|
| 17 | Final Exams | Ölçme Yöntemleri: Yazılı Sınav |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 5 | 70 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 15 | 15 |
| Final Exam | 1 | 30 | 30 |
| Total Workload (Hour) | 157 | ||
| Total Workload / 25 (h) | 6,28 | ||
| ECTS | 6 ECTS | ||