PAÜ .:. Eğitim Öğretim Bilgi Sistemi

COURSE INFORMATION

Course Code	Course Title	L+P Hour	Semester	ECTS
EKNM 206	OPEN SOURCE CODE PROGRAMMING	2 + 2	4th Semester	5,5

COURSE DESCRIPTION

Course Level	Bachelor's Degree
Course Type	Compulsory
Course Objective	Students will be able to recognize the interfaces of the platforms related to R software, download the necessary packages, read the data sets in different formats, edit the data sets and apply statistical operations, gain the skills to present the calculated statistics with tables and graphs.
Course Content	Introduction to R software, the basics of R, summarizing data with R, Data analysis with R, Developing and visualizing statistical model.
Prerequisites	No the prerequisite of lesson.
Corequisite	No the corequisite of lesson.
Mode of Delivery	Face to Face

COURSE LEARNING OUTCOMES

1	Knows the importance of effective use of R language for data analysis.
2	Understands the steps required for data analysis.
3	Prepare data with R programming language and make statistical modeling.

COURSE'S CONTRIBUTION TO PROGRAM

Data not found.

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION

Activities	Quantity	Duration (Hour)	Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)	14	3	42
Hours for off-the-classroom study (Pre-study, practice)	14	3	42
Mid-terms	1	29	29
Final examination	1	30	30
Total Work Load ECTS Credit of the Course			143 5,5

COURSE DETAILS

Select Year

Course Details

Course Code	Course Title	L+P Hour	Course Code	Language Of Instruction	Course Semester
EKNM 206	OPEN SOURCE CODE PROGRAMMING	2 + 2	1	Turkish	2023-2024 Spring

Course Coordinator	E-Mail	Phone Number	Course Location	Attendance
Assoc. Prof. Dr. FERDA ESİN GÜLEL	fegulel@pau.edu.tr		İİBF C0017	%60

Goals		Students will be able to recognize the interfaces of the platforms related to R software, download the necessary packages, read the data sets in different formats, edit the data sets and apply statistical operations, gain the skills to present the calculated statistics with tables and graphs.
Content		Introduction to R software, the basics of R, summarizing data with R, Data analysis with R, Developing and visualizing statistical model.

Topics

Weeks	Topics
1	Introduction to R Studio, Data Import, Vector-Matrice Input
2	Install Package, Logic Statement, Descriptive Statistics, Setting Working Directory
3	Plot, Histogram, Pie Chart, Bar Chart
4	Boxplot, Scatter Plot
5	Plot Editing
6	Probability Distributions
7	Midterm
8
9
10
11
12
13
14

Materials

Materials are not specified.

Resources

Resources	Resources Language
Bilgisayar Bilimleri, Nobel Yayın ve Dağıtım	Türkçe
R ile Programlama, Burak Özkan, Yalçın Özkan, Papatya Bilim.	Türkçe
R ile Uygulamalı İstatistik, İbrahim Demir, Papatya Bilim.	Türkçe
Veri Biliminde R ile Veri Önişleme, Zeynel Cebeci, Nobel Yayın ve Dağıtım.	Türkçe

Course Assessment

Assesment Methods	Percentage (%)	Assesment Methods Title
Final Exam	60	Final Exam
Midterm Exam	40	Midterm Exam

L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes

Prospective Student