TÜRKÇE
ENGLISH
Information
| Code | BBT414 |
| Name | Applied Data Analysis |
| Term | 2023-2024 Academic Year |
| Semester | 8. Semester |
| Duration (T+A) | 0-2 (T-A) (17 Week) |
| ECTS | 3 ECTS |
| National Credit | 1 National Credit |
| Teaching Language | Türkçe |
| Level | Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. ALKHAN SARIYEV |
| Course Instructor |
Prof. ALKHAN SARIYEV
(A Group)
(Ins. in Charge)
|
Course Goal / Objective
The aim of this course is to enable students to gain knowledge about the presentation of data, summarizing and analysis of data by taking the concepts that form the basis of statistics practically.
Course Content
Data, Data Collection and Description, Data editing and presentation methods, 3D graphics of data, Data-based interpolation and transformation of functions, Data base and data filtering management systems, Statistical data analysis, Regression and correlation, Multiple regression and functional forms, Analysis of variance based on data, Analysis of principal components of data within a cluster, Dendrogram
Course Precondition
No prerequisites.
Resources
Data Analysis with Examples SPSS Applied
Notes
Different resources on data analysis
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Find and develop appropriate tools and methods to collect data correctly |
| LO02 | Produce information by summarizing data in a way that helps decision making |
| LO03 | Do basic and advanced statistical data analysis |
| LO04 | Produce information by processing data stored in information systems |
| LO05 | Use information technologies and software in data management and analysis |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Has discipline-specific subject’s adequate knowledge of mathematics, science, and Agricultural Engineering (Soil Science and Plant Nutrition); use theoretical and applied knowledge in these fields of the complex engineering problems. | |
| PLO02 | Beceriler - Bilişsel, Uygulamalı | Define, formulate and solve complex problems in the field of Soil Science and Plant Nutrition, select and apply appropriate analysis and modeling methods for this purpose. | |
| PLO03 | Yetkinlikler - Öğrenme Yetkinliği | Design a complex system, process, device or product to meet specific requirements under realistic constraints and conditions, and apply modern design methods for this purpose in Soil Science and Plant Nutrition discipline. | |
| PLO04 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Select and use modern tools necessary for the analysis and solution of complex problems and use information technologies effectively in the field of Soil Science and Plant Nutrition application. | 2 |
| PLO05 | Beceriler - Bilişsel, Uygulamalı | Design, conduct experiments, collect data, analyze and interpret results for the study of complex problems or discipline-specific research issues encountered in the field of Soil Science and Plant Nutrition. | 2 |
| PLO06 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Work effectively in interdisciplinary (Soil Science and Plant Nutrition) and multidisciplinary teams; develope individual study skills | |
| PLO07 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Communicate effectively orally and in writing; has a foreign language knowledge at the “beginner” level; write reports effectively in the field of Soil Science and Plant Nutrition, understand written reports, prepare, design and production reports, make effective presentations, take and give clear and understandable instructions. | |
| PLO08 | Yetkinlikler - Öğrenme Yetkinliği | Gain awareness of the necessity of lifelong learning; access information in the field of Soil Science and Plant Nutrition, follow the developments in science and technology, and constantly renew oneself. | |
| PLO09 | Yetkinlikler - Alana Özgü Yetkinlik | Compliance with ethical principles, professional and ethical responsibility in the field of Soil Science and Plant Nutrition, and has knowledge of standards used in engineering practices. | |
| PLO10 | Yetkinlikler - Alana Özgü Yetkinlik | Gain knowledge of business practices as project and risk management and change management; gain awareness of entrepreneurship and innovation; information about sustainable development in the field of Soil Science and Plant Nutrition. | |
| PLO11 | Yetkinlikler - Alana Özgü Yetkinlik | Has information about the effects of Soil Science and Plant Nutrition practice’s on health, environmental, and security in universal scale and social dimensions: The problems of the age reflection related with the field of Soil Science and Plant Nutrition; gain awareness of the legal implications of Soil Science and Plant Nutrition solutions. |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Data and Units, Unit Conversions, Data Mining, Data Storage, Large Data Transfer and Data Security | Basic statistics and assessment and evaluation information | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Bireysel Çalışma, Problem Çözme |
| 2 | Data, Data Collection and Description and Clustering | Basic statistics and assessment and evaluation information | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Bireysel Çalışma, Problem Çözme |
| 3 | Graphical Analysis of Data, 3-dimensional graphical analysis | Basic statistics and assessment and evaluation information | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Bireysel Çalışma, Problem Çözme |
| 4 | Data-based interpolation and function transformation | Basic statistics and assessment and evaluation information | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Bireysel Çalışma, Problem Çözme |
| 5 | Database and data filtering management systems | Basic statistics and assessment and evaluation information | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Bireysel Çalışma, Problem Çözme |
| 6 | Linear Regression and Correlation Analysis | Basic statistics and assessment and evaluation information | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Bireysel Çalışma, Problem Çözme |
| 7 | Preparing for the exam | Preparing for the exam | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Bireysel Çalışma, Problem Çözme |
| 8 | Mid-Term Exam | Ölçme Yöntemleri: Yazılı Sınav |
|
| 9 | Multiple regression and functional transformations-1 | Basic statistics and assessment and evaluation information | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Bireysel Çalışma, Problem Çözme |
| 10 | Multiple regression and functional transformations-2 | Basic statistics and assessment and evaluation information | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Bireysel Çalışma, Problem Çözme |
| 11 | One-Way Analysis of Variance Based on Data-1 | Basic statistics and assessment and evaluation information | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Bireysel Çalışma, Problem Çözme |
| 12 | One-Way Analysis of Variance Based on Data-2 | Basic statistics and assessment and evaluation information | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Bireysel Çalışma, Problem Çözme |
| 13 | Principal component analysis of data within a cluster-1 | Basic statistics and assessment and evaluation information | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Bireysel Çalışma, Problem Çözme |
| 14 | Principal component analysis of data within a cluster-2, Dendrogram (Branching) scheme | Basic statistics and assessment and evaluation information | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Bireysel Çalışma, Problem Çözme |
| 15 | Preparing for the exam | Preparing for the exam | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Bireysel Çalışma, Problem Çözme |
| 16 | Term Exams | Ölçme Yöntemleri: Yazılı Sınav |
|
| 17 | Term Exams | Ölçme Yöntemleri: Yazılı Sınav |
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 | ||