Information Package / Course Catalogue
Statistical Modeling and Programming in R
Course Code: BİS636
Course Type: Area Elective
Couse Group: Third Cycle (Doctorate Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 3
Prt.: 2
Credit: 4
Lab: 0
ECTS: 5
Objectives of the Course

Open source R statistical programming language, the language is spreading rapidly all over the world. In this respect, promote and statistics students to learn the language which is free of charge, to gain the ability to use and develop programs in a variety of applications in statistics

Course Content

To the R programming language and statistical applications. Statistical graphics çizdirilebilmesi course content easily.

Name of Lecturer(s)
Learning Outcomes
1.R statistical language to run programs, to develop codes and gives students the knowledge and skills to make these statistical applications.
2.To understand R codes in statistics
3.To summarize the dataset with R
4.R ile Grafik çizebilme
5.Perform statistical analysis with R
Recommended or Required Reading
Weekly Detailed Course Contents
Week 1 - Theoretical
The introduction of the R language
Week 1 - Practice
Applications with R
Week 2 - Theoretical
The installation of R
Week 2 - Practice
Applications with R
Week 3 - Theoretical
Starting with R program code
Week 3 - Practice
Applications with R
Week 4 - Theoretical
Descriptive statistical analysis with R
Week 4 - Practice
Applications with R
Week 5 - Theoretical
Descriptive statistical analysis with R
Week 5 - Practice
Applications with R
Week 6 - Theoretical
Plotting with R
Week 6 - Practice
Applications with R
Week 7 - Theoretical
Plotting with R
Week 7 - Practice
Applications with R
Week 8 - Theoretical
Literature review and discussion (Midterm exam)
Week 9 - Theoretical
Univariate analyses with R
Week 9 - Practice
Applications with R
Week 10 - Theoretical
Univariate analyses with R
Week 10 - Practice
Applications with R
Week 11 - Theoretical
Multivariate analyses with R
Week 11 - Practice
Applications with R
Week 12 - Theoretical
Multivariate analyses with R
Week 12 - Practice
Applications with R
Week 13 - Theoretical
Multivariate analyses with R
Week 13 - Practice
Applications with R
Week 14 - Theoretical
Multivariate analyses with R
Week 14 - Practice
Applications with R
Week 15 - Final Exam
Final exam
Assessment Methods and Criteria
Type of AssessmentCountPercent
Attending Lectures1%5
Assignment1%5
Midterm Examination1%20
Final Examination1%70
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory140342
Lecture - Practice140228
Assignment1505
Quiz2216
Midterm Examination115217
Final Examination120222
TOTAL WORKLOAD (hours)120
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
OÇ-1
4
4
4
4
4
4
5
OÇ-2
5
4
4
4
4
4
4
OÇ-3
4
4
3
4
4
4
4
OÇ-4
5
4
4
4
4
4
4
OÇ-5
5
5
5
4
4
4
5
Adnan Menderes University - Information Package / Course Catalogue
2026