MN0017 Statistical Modeling in Material Science

6 ECTS - 3-0 Duration (T+A)- . Semester- 3 National Credit

Information

Code MN0017
Name Statistical Modeling in Material Science
Semester . Semester
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 Goal

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