ISB365 Statistical Application in MatLab

3 ECTS - 2-0 Duration (T+A)- 5. Semester- 2 National Credit

Information

Code ISB365
Name Statistical Application in MatLab
Term 2023-2024 Academic Year
Semester 5. Semester
Duration (T+A) 2-0 (T-A) (17 Week)
ECTS 3 ECTS
National Credit 2 National Credit
Teaching Language Türkçe
Level Lisans Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Doç. Dr. SELMA TOKER KUTAY
Course Instructor Doç. Dr. SELMA TOKER KUTAY (A Group) (Ins. in Charge)


Course Goal / Objective

The aim of this course is to teach the basics of the MATLAB program and gain the ability to apply basic statistical knowledge using this program.

Course Content

Introduction to MATLAB program, Data analysis, Graphs, Statistical data analysis, Descriptive statistics and tables, Operations on mathematical functions, Data derivation and distribution fitting are included in this course.

Course Precondition

None

Resources

MATLAB ve İstatistiksel Veri Analizi, İpek DEVECİ KOCAKOÇ, Nobel Yayınevi, Şubat 2015

Notes

Lecture Notes


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Learns the basics of the MATLAB program.
LO02 Learns to do the statistical data analysis with MATLAB program.
LO03 Learns fitting distribution to data.
LO04 Learns to do operations related to mathematical functions.


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal Explain the essence fundamentals and concepts in the field of Probability, Statistics and Mathematics 2
PLO02 Bilgi - Kuramsal, Olgusal Emphasize the importance of Statistics in life 2
PLO03 Bilgi - Kuramsal, Olgusal Define basic principles and concepts in the field of Law and Economics
PLO04 Bilgi - Kuramsal, Olgusal Produce numeric and statistical solutions in order to overcome the problems 3
PLO05 Bilgi - Kuramsal, Olgusal Use proper methods and techniques to gather and/or to arrange the data 4
PLO06 Bilgi - Kuramsal, Olgusal Utilize computer systems and softwares 3
PLO07 Bilgi - Kuramsal, Olgusal Construct the model, solve and interpret the results by using mathematical and statistical tehniques for the problems that include random events 3
PLO08 Bilgi - Kuramsal, Olgusal Apply the statistical analyze methods 4
PLO09 Bilgi - Kuramsal, Olgusal Make statistical inference(estimation, hypothesis tests etc.) 3
PLO10 Bilgi - Kuramsal, Olgusal Generate solutions for the problems in other disciplines by using statistical techniques 3
PLO11 Bilgi - Kuramsal, Olgusal Discover the visual, database and web programming techniques and posses the ability of writing programme 4
PLO12 Bilgi - Kuramsal, Olgusal Construct a model and analyze it by using statistical packages 4
PLO13 Beceriler - Bilişsel, Uygulamalı Distinguish the difference between the statistical methods 3
PLO14 Beceriler - Bilişsel, Uygulamalı Be aware of the interaction between the disciplines related to statistics 2
PLO15 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Make oral and visual presentation for the results of statistical methods 4
PLO16 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Have capability on effective and productive work in a group and individually 3
PLO17 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Professional development in accordance with their interests and abilities, as well as the scientific, cultural, artistic and social fields, constantly improve themselves by identifying training needs
PLO18 Yetkinlikler - Öğrenme Yetkinliği Develop scientific and ethical values in the fields of statistics-and scientific data collection 3


Week Plan

Week Topic Preparation Methods
1 Introduction to MATLAB program Source reading Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
2 The MATLAB desktop and sample program Review of the previous lecture, Source reading Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
3 Importing and exporting data Review of the previous lecture, Source reading Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
4 Processing with missing data Review of the previous lecture, Source reading Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
5 Introduction to Graphics Review of the previous lecture, Source reading Öğretim Yöntemleri:
Anlatım, Tartışma
6 Basic 2-D graphs and 3-D plots Review of the previous lecture, Source reading Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
7 Introduction to statistical data analysis Review of the previous lecture, Source reading Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
8 Midterm Exam General review Öğretim Yöntemleri:
Problem Çözme
9 Obtaining descriptive statistics Review of the previous lecture, Source reading Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
10 Creating a frequency table and a cross table Review of the previous lecture, Source reading Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
11 Graphical representation of the data Review of the previous lecture, Source reading Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
12 Introduction to simulation Review of the previous lecture, Source reading Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
13 Random number generation and Normal random numbers Review of the previous lecture, Source reading Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
14 Distribution fitting Review of the previous lecture, Source reading Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
15 Operations related to mathematical functions Review of the previous lecture, Source reading Öğretim Yöntemleri:
Anlatım, Tartışma, Problem Çözme
16 Final Term Exam Review the topics discussed in the lecture notes and sources Ölçme Yöntemleri:
Yazılı Sınav, Ödev
17 Final Term Exam Review the topics discussed in the lecture notes and sources Ölçme Yöntemleri:
Yazılı Sınav, Ödev


Student Workload - ECTS

Works Number Time (Hour) Workload (Hour)
Course Related Works
Class Time (Exam weeks are excluded) 14 2 28
Out of Class Study (Preliminary Work, Practice) 14 2 28
Assesment Related Works
Homeworks, Projects, Others 0 0 0
Mid-term Exams (Written, Oral, etc.) 1 6 6
Final Exam 1 16 16
Total Workload (Hour) 78
Total Workload / 25 (h) 3,12
ECTS 3 ECTS

Update Time: 02.05.2023 08:47