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Information
| Code | ST0053 |
| Name | Data Visualization and Producing Graphics With R |
| Semester | . Semester |
| Duration (T+A) | 2-2 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Yüksek Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator |
Course Goal
Data visualization is the process producing graphics from data in order to increase the clarity and comprehensibility of information. This process is a crucial step in reporting and presenting the scientific data because high quality graphics can significantly improve the probability of publication. R is an open source language and environment for statistical computing and recently, it is one of the most favorite software in data visualization. With thousands of libraries, R presents almost limitless options on producing graphics. This course will develop advanced skills in producing high quality R plots using base functions and ggplot library. Required R usage skills will be introduced during the course.
Course Content
Basics of R usage, grammar of R graphics, scatter plots, line plots and smoothers, box plots, bar charts and stacked bar charts, pie charts, mapping applications in R environment, bubble charts and word clouds, working with graphic layers and hybridize different graphic types, managing data labels and legends, enhancing visual quality with shapes, expressions and data tables, working with multiple plot grids
Course Precondition
Successful completion of a lecture on Introductory Level Statistics
Resources
Data Visualization with R, https://rkabacoff.github.io/datavis/ R Graphics Cookbook https://r-graphics.org/
Notes
Online Book: R Graphics Cookbook http://www.cookbook-r.com/Graphs/
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Gain knowledge on R terminal, R Studio and R Commander graphical user interfaces |
| LO02 | Gain basic R usage skills |
| LO03 | Produce publication level graphics such as scatter, line, box, pie, and bubble plots, using base functions and ggplot library |
| LO04 | Can make basic maps with R |
| LO05 | Gain skills of working with graphic layers and grids |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Improves theoretical and practical knowledge in the field of Marine and Inland Water Biology and Fisheries Basic Sciences. | 2 |
| PLO02 | Bilgi - Kuramsal, Olgusal | Comprehends interactions between Fisheries Basic Sciences and other disciplines. | 2 |
| PLO03 | Bilgi - Kuramsal, Olgusal | Determines strategies and investigates methods about their field of study in Fisheries Basic Science. | 3 |
| PLO04 | Bilgi - Kuramsal, Olgusal | Produces new information and theories by interpreting and synthesising the information from other disciplines and uses the theoretical and practical information from their field of study in Fisheries Basic Science. | |
| PLO05 | Bilgi - Kuramsal, Olgusal | Collects data, interprets results and suggests solutions by using dialectic research methodology in the certain field of Marine and Inland Water Biology and Fisheries Basic Sciences. | 5 |
| PLO06 | Bilgi - Kuramsal, Olgusal | Independently plans, designs and performs a certain project in the field of Fisheries Basic Sciences. | 2 |
| PLO07 | Bilgi - Kuramsal, Olgusal | Produces solutions by improving new strategic approaches and taking responsibilities for the potential problems in the field of study as an individual or team member. | 1 |
| PLO08 | Beceriler - Bilişsel, Uygulamalı | Determines the requirements for Fishery Basic Science education, reaches the resources, critically interpretes knowledge and skills and gains experience to direct the education. | 3 |
| PLO09 | Beceriler - Bilişsel, Uygulamalı | Has positive stance on the lifelong education and uses it for the public benefit by using the gained theoretical and practical knowledge in the field of Marine and Inland Water Biology and Fisheries Basic Sciences. | 2 |
| PLO10 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Follows the current topics and improvements in the field of Fisheries Basic Sciences, publishes and presents the research results, contributes to constitution of a public conscience in the field of interest. | 5 |
| PLO11 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Effectively communicates about the field of Marine and Inland Water Biology and Fisheries Basic Sciences by using written and oral presentation tools, follows up and criticizes the meetings and seminars. | 4 |
| PLO12 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Follows up international publications and communicates with international collaborators by using language skills. | 1 |
| PLO13 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Uses the communication and information technologies about the field of interest in an advanced level. | 5 |
| PLO14 | Yetkinlikler - Öğrenme Yetkinliği | Conforms, controls and teaches social, cultural and scientific ethics in the investigation and publication process of the data related with the field of interest. | 4 |
| PLO15 | Yetkinlikler - Öğrenme Yetkinliği | Improves strategies, politics and application codes by following scientific and technological developments on the certain field of Marine and Inland Water Biology and Fisheries Basic Sciences. Investigates and extends the results on behalf of public in frame of total quality management process. | 1 |
| PLO16 | Yetkinlikler - Öğrenme Yetkinliği | Uses the abilities and experiences on applications and solving problems that gained during the MSc education for the interdisciplinary studies. | 4 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Basics of R environment and graphical user interfaces (GUI) | Attendants should install R Terminal, and R Studio and R Commander GUIs | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 2 | Grammar of R graphics | Sample data will be prepared | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 3 | Scatter plots | Sample data will be prepared | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 4 | Line plots and smoothers | Sample data will be prepared | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 5 | Box plots | Sample data will be prepared | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 6 | Bar charts and stacked bar charts | Sample data will be prepared | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 7 | Pie charts | Sample data will be prepared | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 8 | Mid-Term Exam | Öğretim Yöntemleri: Alıştırma ve Uygulama |
|
| 9 | Mapping applications in R environment | Sample data will be prepared | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 10 | Bubble charts and word clouds | Sample data will be prepared | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 11 | Working with graphic layers and hybridize different graphic types-1 | Sample data will be prepared | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 12 | Working with graphic layers and hybridize different graphic types-2 | Sample data will be prepared | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 13 | Managing data labels and legends in R plots | Sample data will be prepared | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 14 | Enhancing visual quality with shapes, expressions and data tables | Sample data will be prepared | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 15 | Working with multiple plot grids | Sample data will be prepared | Öğretim Yöntemleri: Anlatım, Problem Çözme |
| 16 | Term Exams | Ölçme Yöntemleri: Ödev |
|
| 17 | Term Exams | Ölçme Yöntemleri: Ödev |
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 | 4 | 56 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 1 | 2 | 2 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 12 | 12 |
| Final Exam | 1 | 28 | 28 |
| Total Workload (Hour) | 154 | ||
| Total Workload / 25 (h) | 6,16 | ||
| ECTS | 6 ECTS | ||