ISTINYE UNIVERSITY BİLGİ PAKETİ / DERS KATALOĞU
Course Introduction and Application Information
| Course Code: | UNI327 | ||||
| Course Name: | Data Analysis with R | ||||
| Semester: | Spring | ||||
| Course Credits: |
|
||||
| Language of instruction: | Turkish | ||||
| Course Condition: | |||||
| Does the Course Require Work Experience?: | No | ||||
| Type of course: | Departmental Elective | ||||
| Course Level: |
|
||||
| Mode of Delivery: | E-Learning | ||||
| Course Coordinator: | Öğr. Gör. AYŞEGÜL ÇALIŞKAN İŞCAN | ||||
| Course Lecturer(s): | Dr. Ayşegül Çalışkan İşcan | ||||
| Course Assistants: |
Course Objective and Content
| Course Objectives: | This course aims to teach the R programming language at a basic level. |
| Course Content: | This course includes basic elements of R programming languages. |
Learning Outcomes
|
The students who have succeeded in this course;
1) Have knowledge about R programming language 2) Learns R programming language at a basic level. 3) Can analyze any data by using R language. 4) Can understand and manipulate any R code. 5) Can make statistical analysis by using R language. |
Course Flow Plan
| Week | Subject | Related Preparation |
| 1) | Course overview | |
| 2) | R Arithmetic, Atomic Data Types | |
| 3) | Variables, Vectors | |
| 4) | Matrices | |
| 5) | Lists, Data Frames | |
| 6) | Factors, Reading and Writing Data | |
| 7) | Exercises, Lesson Repetition | |
| 8) | Mid-term Week | |
| 9) | Control flow, functions | |
| 10) | Exploring and Preparing Data | |
| 11) | Working with text data | |
| 12) | Preparing Numeric Data, Dealing with Dates | |
| 13) | Merging data, Frequency tables | |
| 14) | Plotting in Base R, plotting with ggplot2 |
Sources
| Course Notes / Textbooks: | 1. Mark Gardener - Beginning R_ The Statistical Programming Language-Wrox 2. Tony Fischetti - Data Analysis with R_ Load, wrangle, and analyze your data using the world's most powerful statistical programming language-Packt Publishing (2015) |
| References: | 1. Mark Gardener - Beginning R_ The Statistical Programming Language-Wrox 2. Tony Fischetti - Data Analysis with R_ Load, wrangle, and analyze your data using the world's most powerful statistical programming language-Packt Publishing (2015) |
Course - Program Learning Outcome Relationship
| Course Learning Outcomes | 1 |
2 |
3 |
4 |
5 |
|---|---|---|---|---|---|
| Program Outcomes |
Course - Learning Outcome Relationship
| No Effect | 1 Lowest | 2 Average | 3 Highest |
| Program Outcomes | Level of Contribution |
Assessment & Grading
| Değerlendirme Yöntemleri ve Kriterleri | Number of Activities | Level of Contribution |
| Application | 13 | % 20 |
| Midterms | 1 | % 30 |
| Final | 1 | % 50 |
| total | % 100 | |
Workload and ECTS Credit Calculation
| Activities | Number of Activities | Workload |
| Course Hours | 15 | 45 |
| Study Hours Out of Class | 16 | 16 |
| Project | 1 | 8 |
| Midterms | 1 | 1 |
| Total Workload | 70 | |