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Information
| Code | MG3819 |
| Name | Data Analysis |
| Term | 2024-2025 Academic Year |
| Term | Fall and Spring |
| Duration (T+A) | 4-0 (T-A) (17 Week) |
| ECTS | 8 ECTS |
| National Credit | 4 National Credit |
| Teaching Language | Türkçe |
| Level | Doktora Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Doç. Dr. MEHMET ALİ BURAK NAKIBOĞLU |
| Course Instructor |
1 |
Course Goal / Objective
The aim of this course is to make students capable of using suitable and appropriate data analysis methods for different research objectives and cases, according to each methods' specific application rules and processes.
Course Content
This course consists of the subjects of examining the data, descriptive statistics, factor analysis, regression, discriminant, multivariate variance, cluster analysis and basics of structural equation modeling
Course Precondition
No prerequisite for the course
Resources
Hair, J.F.; Black, W.C.; Babin, B.J.; Anderson, R.E.; Tahtam, R.L. Multivariate Data Analysis Sharma, S. Applied Multivariate Techniques Nakip M., Pazarlama Araştırmaları Teknikler Ve SPSS Destekli Uygulamalar Mcdaniel, C., Gates R., Marketing Research Essentials Journal Of Marketing, Journal Of Marketing Research
Notes
Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking Foster Provots Tom Fawcett
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Defines the basics of basic data analysis methods |
| LO02 | List multivariate analyzes and their assumptions |
| LO03 | describes the application processes of multivariate analyzes and related tests |
| LO04 | Uses statistical package programs and analyze data through parametric methods and evaluate all the results in the light of methodological rules and approaches. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Explains the basic theoretical models for business field | |
| PLO02 | Bilgi - Kuramsal, Olgusal | Lists and identifies the theories that will contribute to the development of scientific methods and tools used in business | |
| PLO03 | Bilgi - Kuramsal, Olgusal | Has an understanding of the legal and ethical issues faced by the Business profession | |
| PLO04 | Bilgi - Kuramsal, Olgusal | Explains how to interpret the findings as a result of models used in business methods. | 5 |
| PLO05 | Bilgi - Kuramsal, Olgusal | Creates sufficient knowledge to find a solution to the problems met by business | |
| PLO06 | Bilgi - Kuramsal, Olgusal | Contributes to business by following the basic steps of the methods used in business | 3 |
| PLO07 | Bilgi - Kuramsal, Olgusal | Apply the application of business management methods. | 3 |
| PLO08 | Bilgi - Kuramsal, Olgusal | Encourages taking responsibility, claiming the lead and working effectively in a team and / or individually. | 5 |
| PLO09 | Beceriler - Bilişsel, Uygulamalı | Keeps track of the latest developments in the field as a recognition of the need for lifelong learning and constant renewal | |
| PLO10 | Beceriler - Bilişsel, Uygulamalı | Utilizes scientific sources in the field, collect the data, synthesizes the obtained information and presents the outcomes effectively | 5 |
| PLO11 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Has a good command of Turkish, as well as at least one another foreign language in accordance with the requirements of academic and work life | 4 |
| PLO12 | Yetkinlikler - Öğrenme Yetkinliği | Develops and implements new research methods that will contribute to the development of the business field | |
| PLO13 | Yetkinlikler - Öğrenme Yetkinliği | Develops new guidelines for the business managers’ decision making processes by researching on sub-disciplines of the business field. | |
| PLO14 | Yetkinlikler - Öğrenme Yetkinliği | Forms the basis for the decision-making process by researching on the science of business field |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Introduction to Data Analysis | Reading related topics | Öğretim Yöntemleri: Anlatım |
| 2 | Types of Data Analysis | Reading related topics | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 3 | Classification of Techniques | Reading related topics | Öğretim Yöntemleri: Anlatım |
| 4 | Examining the Data: Graphical Examination | Reading related topics | Öğretim Yöntemleri: Anlatım, Gösterip Yaptırma |
| 5 | Examining the Data: Missing Data and Outliers | Reading related topics, solving examples | Öğretim Yöntemleri: Anlatım, Gösterip Yaptırma |
| 6 | Examining the Data:Testing Assumptions of Techniques | Reading related chapters, solving problems | Öğretim Yöntemleri: Anlatım, Gösterip Yaptırma |
| 7 | Factor Analysis | Reading related topics, solving examples | Öğretim Yöntemleri: Anlatım, Gösterip Yaptırma, Problem Çözme |
| 8 | Mid-Term Exam | Studying | Ölçme Yöntemleri: Yazılı Sınav |
| 9 | Dependence Techniques: Regression Analysis I | Reading related topics | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 10 | Dependence Techniques: Regression Analysis II | Reading related topics, solving examples | Öğretim Yöntemleri: Anlatım, Gösterip Yaptırma, Problem Çözme |
| 11 | Dependence Techniques: Discriminant Analysis | Reading related topics | Öğretim Yöntemleri: Anlatım, Gösterip Yaptırma, Problem Çözme |
| 12 | Dependence Techniques: Analysis of Variance | Reading related topics | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 13 | Interdependence Techniques: Cluster Analysis | Reading related topics | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 14 | Advanced Techniques: Structural Equation Modeling (S.E.M.) I | Reading related topics | Öğretim Yöntemleri: Anlatım |
| 15 | Advanced Techniques: Structural Equation Modeling (S.E.M.) II | Reading related topics, solving examples | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 16 | Term Exams | Studying | Ölçme Yöntemleri: Yazılı Sınav |
| 17 | Term Exams | Studying | Ölçme Yöntemleri: Yazılı Sınav |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 4 | 56 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 8 | 112 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 2 | 4 | 8 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 12 | 12 |
| Final Exam | 1 | 24 | 24 |
| Total Workload (Hour) | 212 | ||
| Total Workload / 25 (h) | 8,48 | ||
| ECTS | 8 ECTS | ||