E-Commerce and Marketing | |||||
Associate | TR-NQF-HE: Level 5 | QF-EHEA: Short Cycle | EQF-LLL: Level 5 |
Course Code: | UNI327 | ||||
Course Name: | Data Analysis with R | ||||
Semester: | Spring | ||||
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. |
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 |
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Program Outcomes | |||||
1) To have the ability to understand and apply basic concepts in the field of e-commerce and marketing | |||||
2) Having the ability to catch up with the speed of the digital age and keep their information up to date | |||||
3) Having detailed technical and professional application skills in subjects such as mobile marketing, digital media marketing, social media usage, digital analysis and measurement. |
No Effect | 1 Lowest | 2 Average | 3 Highest |
Program Outcomes | Level of Contribution | |
1) | To have the ability to understand and apply basic concepts in the field of e-commerce and marketing | 2 |
2) | Having the ability to catch up with the speed of the digital age and keep their information up to date | 1 |
3) | Having detailed technical and professional application skills in subjects such as mobile marketing, digital media marketing, social media usage, digital analysis and measurement. | 2 |
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 |