International Trade and Business (English)
Bachelor TR-NQF-HE: Level 6 QF-EHEA: First Cycle EQF-LLL: Level 6

Course Introduction and Application Information

Course Code: UNI280
Course Name: Data Analysis with R 
Semester: Spring
Course Credits:
ECTS
5
Language of instruction: English
Course Condition:
Does the Course Require Work Experience?: No
Type of course: University Elective
Course Level:
Bachelor TR-NQF-HE:6. Master`s Degree QF-EHEA:First Cycle EQF-LLL:6. Master`s Degree
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
1) Has a broad and interdisciplinary perspective on international business and trade by the use of social sciences and mathematics,
2) Possess the knowledge and skills related to different functions and interactions of international business and trade.
3) Possess the knowledge and skills to interpret the data, concepts and ideas in the field of international business and trade with scientific and technological methods.
4) Use different theoretical approaches to understanding and solving various business and trade problems.
5) Explains the competitiveness of the countries with the requirements of international competition and interprets the functioning of the actors and regulatory structures in the international environment.
6) Understands the value of developing new trade projects and generating strategies within international market needs.
7) Solves complex business and global trade problems by using various statistical techniques and numerical methods and makes analyzes by using statistical programs effectively.
8) Uses a foreign language at the B1 General Level in terms of European Language Portfolio criteria according to the level of education.
9) Develops teamwork, negotiation, leadership and entrepreneurship skills.
10) Possess the knowledge of universal ethical values, social responsibility and sufficient legal and regulatory knowledge.
11) Develops positive attitudes related to lifelong learning and identifies individual learning needs and carries out studies to correct them.
12) Students will be able to communicate their ideas and solutions both written and orally, and present and publish them on both national and international platforms.
13) Uses information and communication technologies together with computer software at the advanced level of European Computer Using License required by the field.

Course - Learning Outcome Relationship

No Effect 1 Lowest 2 Average 3 Highest
       
Program Outcomes Level of Contribution
1) Has a broad and interdisciplinary perspective on international business and trade by the use of social sciences and mathematics,
2) Possess the knowledge and skills related to different functions and interactions of international business and trade.
3) Possess the knowledge and skills to interpret the data, concepts and ideas in the field of international business and trade with scientific and technological methods.
4) Use different theoretical approaches to understanding and solving various business and trade problems.
5) Explains the competitiveness of the countries with the requirements of international competition and interprets the functioning of the actors and regulatory structures in the international environment.
6) Understands the value of developing new trade projects and generating strategies within international market needs.
7) Solves complex business and global trade problems by using various statistical techniques and numerical methods and makes analyzes by using statistical programs effectively.
8) Uses a foreign language at the B1 General Level in terms of European Language Portfolio criteria according to the level of education.
9) Develops teamwork, negotiation, leadership and entrepreneurship skills.
10) Possess the knowledge of universal ethical values, social responsibility and sufficient legal and regulatory knowledge.
11) Develops positive attitudes related to lifelong learning and identifies individual learning needs and carries out studies to correct them.
12) Students will be able to communicate their ideas and solutions both written and orally, and present and publish them on both national and international platforms.
13) Uses information and communication technologies together with computer software at the advanced level of European Computer Using License required by the field.

Assessment & Grading

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

Workload and ECTS Credit Calculation

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