| Psychology (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: | Fall | ||||
| Course Credits: |
|
||||
| Language of instruction: | English | ||||
| Course Condition: | |||||
| Does the Course Require Work Experience?: | No | ||||
| Type of course: | University 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 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 |
2 |
3 |
4 |
5 |
|||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Program Outcomes | ||||||||||||||
| 1) Have the theoretical knowledge related to major sub areas of psychology. | ||||||||||||||
| 2) Apply psychological concepts and theories in a variety of applied settings. | ||||||||||||||
| 3) Define and explain the cognitive, emotional and behavioral processes of human beings. | ||||||||||||||
| 4) Evaluate psychological evidence and assumptions in a scientific and critical way. | ||||||||||||||
| 5) Collect and analyze psychological research data and interpret and report the findings in accordance to scientific publication rules. | ||||||||||||||
| 6) Develop and utilize assessment and measurement tools for psychological phenomena. | ||||||||||||||
| 7) Have the skills and abilities to follow innovations and developments in psyhology and other related sciences. | ||||||||||||||
| 8) Have knowledge and skills to work effectively on individual or group basis. | ||||||||||||||
| 9) Have knowledge and skills to communicate in a clear and effective manner in national and international settings. | ||||||||||||||
| 10) Behave in accordance with professional code of conduct and ethics related to psychology. | ||||||||||||||
| 11) Behave in an unprejudiced and equal way towards various identity groups such as age, gender, language, race, religion and social class in scientific and professional acitivities. | ||||||||||||||
| 12) Have respect for universal values and human and animal rights. | ||||||||||||||
| 13) Use a foreign language at least B1 level of European Language Portfolio. | ||||||||||||||
| 14) Use computer softwares as well as information and communication technologies at least Basic level of European Computer Driving Licence. | ||||||||||||||
| No Effect | 1 Lowest | 2 Average | 3 Highest |
| Program Outcomes | Level of Contribution | |
| 1) | Have the theoretical knowledge related to major sub areas of psychology. | |
| 2) | Apply psychological concepts and theories in a variety of applied settings. | |
| 3) | Define and explain the cognitive, emotional and behavioral processes of human beings. | |
| 4) | Evaluate psychological evidence and assumptions in a scientific and critical way. | |
| 5) | Collect and analyze psychological research data and interpret and report the findings in accordance to scientific publication rules. | |
| 6) | Develop and utilize assessment and measurement tools for psychological phenomena. | |
| 7) | Have the skills and abilities to follow innovations and developments in psyhology and other related sciences. | |
| 8) | Have knowledge and skills to work effectively on individual or group basis. | |
| 9) | Have knowledge and skills to communicate in a clear and effective manner in national and international settings. | |
| 10) | Behave in accordance with professional code of conduct and ethics related to psychology. | |
| 11) | Behave in an unprejudiced and equal way towards various identity groups such as age, gender, language, race, religion and social class in scientific and professional acitivities. | |
| 12) | Have respect for universal values and human and animal rights. | |
| 13) | Use a foreign language at least B1 level of European Language Portfolio. | |
| 14) | Use computer softwares as well as information and communication technologies at least Basic level of European Computer Driving Licence. |
| 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 | ||||||