Information Package / Course Catalogue
Data Analysis With R
Course Code: EK469
Course Type: Area Elective
Couse Group: First Cycle (Bachelor's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 3
Prt.: 0
Credit: 3
Lab: 0
ECTS: 5
Objectives of the Course

To analyze and interpret statistical problems using R programming language.

Course Content

This lecture aims to teach R programming language and computer aided solutions of the problems related to statistics and probability theory using R programming language.

Name of Lecturer(s)
Learning Outcomes
1.The ability of using R programming languages
2.To be able to generate random numbers
3.The ability of performing the applications of various probability distributions.
4.Drawing graphics with R.
5.To be able to make statistical hypothesis testing with R
Recommended or Required Reading
1.Data Science from Scratch, O’Reilly Media, Joel Grus (2015)
2.Hands-On Machine Learning with Scikit-Learn and TensorFlow, O’Reilly Media, By Aurélien Géron (2017)
Weekly Detailed Course Contents
Week 1 - Theoretical
Installing R and R-Studio Software, R Environment, CRAN Help Commands
Week 2 - Theoretical
R syntax, Variables, Operators, Data Types, Conditional Expressions
Week 3 - Theoretical
Data Structures, Data Frame, Data Frame Query Operations, Receiving Data from External Source, Transferring Data to External Source
Week 4 - Theoretical
Vector and Matrix Operations
Week 5 - Theoretical
Descriptive Statistics with Vectors
Week 6 - Theoretical
Data Visualization
Week 7 - Theoretical
Data Visualization
Week 8 - Theoretical
Data Visualization
Week 9 - Theoretical
Random Variables, Random Number Generation, Probability, Conditional Probability
Week 10 - Theoretical
Discrete and Continuous Probability Distributions
Week 11 - Theoretical
Statistical Analysis in R: Testing Hypothesis I
Week 12 - Theoretical
Statistical Analysis in R: Testing Hypothesis II
Week 13 - Theoretical
Regression Analysis with R
Week 14 - Theoretical
Time Series Analysis in R
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%40
Final Examination1%70
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Practice142370
Individual Work73235
Midterm Examination1819
Final Examination1819
TOTAL WORKLOAD (hours)123
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
OÇ-1
5
4
4
2
2
3
4
5
5
OÇ-2
5
5
5
4
4
4
3
3
3
OÇ-3
5
4
4
4
4
3
3
3
3
OÇ-4
3
3
3
4
4
4
4
3
3
OÇ-5
2
3
3
3
3
4
4
4
4
Adnan Menderes University - Information Package / Course Catalogue
2026