COURSE UNIT TITLE

: STATISTICAL ANALYSIS WITH SOFTWARE

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IND 3942 STATISTICAL ANALYSIS WITH SOFTWARE ELECTIVE 3 0 0 4

Offered By

Industrial Engineering

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSISTANT PROFESSOR ŞEBNEM DEMIRKOL AKYOL

Offered to

Industrial Engineering

Course Objective

The aim of this course is to introduce students to free statistical software programs such as R and to gain the ability to perform statistical analysis such as data analysis, variance analysis, and regression analysis using the software.

Learning Outcomes of the Course Unit

1   To be able to define the general structure of programming with the R language
2   To be able to define the concepts of data entry, vector, and matrix in R
3   Ability to draw statistical graphics
4   To be able to constitute confidence intervals and hypothesis tests in R
5   To be able to apply linear regression and analysis of variance

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to programming with R
2 Basic data structures
3 Extracting, exporting, and saving data
4 Analyzing and manipulating data
5 Generating data graphics and histograms
6 Comparison of population means and variances: Confidence intervals
7 Comparison of population means and variances: Hypothesis tests
8 Mid-term exam
9 One-way ANOVA calculations
10 Two-way ANOVA calculations
11 Regression model building
12 Project presentations
13 Project presentations
14 Project presentations

Recomended or Required Reading

1) YILMAZ, Ö.Ü.A., & YAYIN, K. (2021). R Programlamaya Giriş. KODLAB Yayın Dağıtım Yazılım LTD. ŞTI.
2) ÖZKAN, B. & ÖZKAN, Y. (2017) R ile Programlama, Papatya Yayıncılık Eğitim
3) ARSLAN, I. (2015). R ile istatistiksel programlama. Pusula Yayıncılık

Planned Learning Activities and Teaching Methods

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 PRJ PROJECT
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.25 + PRJ * 0.25 + FIN * 0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.25 + PRJ * 0.25 + RST * 0.50


Further Notes About Assessment Methods

None

Assessment Criteria

Midterm (25%) + Project (25%) + Final Exam (50%)

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Adress: Dokuz Eylül University, Department of Industrial Engineering, Tınaztepe Campus, Buca, Izmir, Türkiye
E-mail: sebnem.demirkol@deu.edu.tr
Tel: +90 232 301 7631

Office Hours

It will be announced in the semester in which the course is opened.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 10 3 30
Preparations before/after weekly lectures 13 2 26
Preparation for midterm exam 1 8 8
Preparation for final exam 1 8 8
Preparing assignments 1 8 8
Preparing presentations 10 2 20
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 104

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11
LO.1444
LO.2545
LO.344
LO.4455
LO.5455