| Automotive Technology | |||||
| Associate | TR-NQF-HE: Level 5 | QF-EHEA: Short Cycle | EQF-LLL: Level 5 | ||
| Course Code: | UNI327 | ||||
| Course Name: | Data Analysis with R | ||||
| Semester: |
Fall Spring |
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| Course Credits: |
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| Language of instruction: | Turkish | ||||
| Course Condition: | |||||
| Does the Course Require Work Experience?: | No | ||||
| Type of course: | University Elective | ||||
| Course Level: |
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| Mode of Delivery: | E-Learning | ||||
| Course Coordinator: | Öğr. Gör. AYŞEGÜL ÇALIŞKAN İŞCAN | ||||
| Course Lecturer(s): | Dr. Ayşegül Çalışkan İşcan | ||||
| Course Assistants: |
| 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. |
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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. |
| 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 |
| 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 Learning Outcomes | 1 |
2 |
3 |
4 |
5 |
|---|---|---|---|---|---|
| Program Outcomes | |||||
| 1) To be one of the Automotive Technicians who have the qualifications needed by the developing and constantly changing automotive industry and other sectors related to automotive industry organizations. | |||||
| 2) New technology recognizes the materials of engine and system elements, finds faults, and uses diagnostic test devices. | |||||
| 3) Has the ability to use basic computer software and hardware and report preparation techniques required by the field. | |||||
| No Effect | 1 Lowest | 2 Average | 3 Highest |
| Program Outcomes | Level of Contribution | |
| 1) | To be one of the Automotive Technicians who have the qualifications needed by the developing and constantly changing automotive industry and other sectors related to automotive industry organizations. | 1 |
| 2) | New technology recognizes the materials of engine and system elements, finds faults, and uses diagnostic test devices. | |
| 3) | Has the ability to use basic computer software and hardware and report preparation techniques required by the field. |
| Semester Requirements | Number of Activities | Level of Contribution |
| Application | 13 | % 20 |
| Midterms | 1 | % 30 |
| Final | 1 | % 50 |
| total | % 100 | |
| PERCENTAGE OF SEMESTER WORK | % 50 | |
| PERCENTAGE OF FINAL WORK | % 50 | |
| total | % 100 | |
| 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 | |