Mathematics (English) | |||||
Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 |
Course Code: | UNI280 | ||||
Course Name: | Data Analysis with R | ||||
Semester: |
Spring Fall |
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Course Credits: |
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Language of instruction: | English | ||||
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. |
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 |
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5 |
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Program Outcomes | |||||||||||
1) Have the knowledge of the scope, history, applications, problems, methods of mathematics and knowledge that will be beneficial to humanity as both scientific and intellectual discipline. | |||||||||||
2) Have the ability to establish a relationship between mathematics and other disciplines and develop mathematical models for interdisciplinary problems. | |||||||||||
3) Have the ability to define, formulate and analyze real life problems with statistical and mathematical techniques. | |||||||||||
4) Have the ability to think analytically and use the time effectively in the process of deduction. | |||||||||||
5) Have the ability to search the literature, understand and interpret scientific articles. | |||||||||||
6) Have the knowledge of basic software to be able to work in the related fields of computer science and have the ability to use information technologies at an advanced level of the European Computer Driving License. | |||||||||||
7) Have the ability to work efficiently in interdisciplinary teams. | |||||||||||
8) Have the ability to communicate effectively in oral and written form, write effective reports and comprehend the written reports, make effective presentations. | |||||||||||
9) Have the consciousness of professional and ethical responsibility and acting ethically; have the knowledge about academic standards. | |||||||||||
10) Have the ability to use a foreign language at least at B1 level in terms of European Language Portfolio criteria. | |||||||||||
11) Are aware of the necessity of lifelong learning; have the ability to access information, to follow developments in science and technology and to constantly renew themselves. |
No Effect | 1 Lowest | 2 Average | 3 Highest |
Program Outcomes | Level of Contribution | |
1) | Have the knowledge of the scope, history, applications, problems, methods of mathematics and knowledge that will be beneficial to humanity as both scientific and intellectual discipline. | |
2) | Have the ability to establish a relationship between mathematics and other disciplines and develop mathematical models for interdisciplinary problems. | |
3) | Have the ability to define, formulate and analyze real life problems with statistical and mathematical techniques. | |
4) | Have the ability to think analytically and use the time effectively in the process of deduction. | |
5) | Have the ability to search the literature, understand and interpret scientific articles. | |
6) | Have the knowledge of basic software to be able to work in the related fields of computer science and have the ability to use information technologies at an advanced level of the European Computer Driving License. | |
7) | Have the ability to work efficiently in interdisciplinary teams. | |
8) | Have the ability to communicate effectively in oral and written form, write effective reports and comprehend the written reports, make effective presentations. | |
9) | Have the consciousness of professional and ethical responsibility and acting ethically; have the knowledge about academic standards. | |
10) | Have the ability to use a foreign language at least at B1 level in terms of European Language Portfolio criteria. | |
11) | Are aware of the necessity of lifelong learning; have the ability to access information, to follow developments in science and technology and to constantly renew themselves. |
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 | Preparation for the Activity | Spent for the Activity Itself | Completing the Activity Requirements | Workload | ||
Course Hours | 13 | 1 | 3 | 1 | 65 | ||
Homework Assignments | 13 | 1 | 1 | 26 | |||
Midterms | 1 | 14 | 1 | 1 | 16 | ||
Final | 1 | 28 | 1 | 1 | 30 | ||
Total Workload | 137 |