COURSE UNIT TITLE

: COMPUTER AIDED DATA ANALYSIS

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
AFY 5046 COMPUTER AIDED DATA ANALYSIS ELECTIVE 3 0 0 5

Offered By

Disaster Administration

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR ISTEM KÖYMEN

Offered to

Disaster Administration

Course Objective

Aim of the Course:
To be able to collect data in the field of disaster management using appropriate methods, to perform statistical evaluations, to interpret the results, to develop skills in using statistical outcomes, to enhance statistical reasoning, and to support these abilities with statistical programming languages.

Learning Outcomes of the Course Unit

1   1- To understand the definition and subject of statistics and its relationship with disaster management
2   2- To explain measures of tendency and measures of variation
3   3- To classify variables according to their characterictics
4   4- To represent and interpret a data set graphically
5   5- To perform and interpret basic statistical analyses
6   6- To define fundamental concepts related to the science of statistics.
7   7- To solve and interpret problems with tos port of programming languages

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 week 1 Introduction to Statistics, Basic Concepts: Statistics, Population, Parameter, Variable, Data
2 week 2 Collection of Data, Classification, Graphical Representations: Frequency Distributions, Pie Charts, Bar Charts, Histogram, Frequency Polygon and Demonstration of the use of basic graphical representations with programming languages
3 week 3 Central Tendency Measures: Demonstration of the use of Arithmetic Mean, Mode, Median, Geometric Mean, Harmonic Mean, Quartiles and Central Tendency Measures with programming languages
4 week 4 Measures of Variability: Range, Standard Deviation, Variance, Absolute Mean Deviation, Coefficient of Variation and demonstration of the use of Variability measures with programming languages
5 week 5 Bowley and Pearson Skewness Measures . Demonstration of the use of asymmetry measures with programming languages
6 week 6 Confidence Intervals, Interpretation and demonstration of their use with programming languages
7 week 7 Hypothesis Testing, Interpretation and demonstration of its use with programming languages
8 week 8 Nonparametric tests, interpretation and demonstration of their use with programming langua
9 week 9 Correlation Analysis and demonstration of its use with programming languages
10 week 10 Regression anad logistic regression Analysis and demonstration of its use with programming languages
11 week 11 Survey resaerch, sample collection
12 week 12 Survey research,, scale development, scale adaptation
13 week 13 Analysis of survey research data with basic methods and sample application with package programs
14 week 14 Scientific article review on the use of basic statistical methods in disaster management

Recomended or Required Reading

1- R ile Istatistiksel Analiz ve Programlama, Nobel Akademik Yayıncılık, Hasan Bulut
2- R ile Veri Analizi, Istatistik, Modelleme,Uygulama, Sentez Yayıncılık, Hakan Emekçi,Suat Altan, Seçkin Yayıncılık
3- SPSS Uygulamalı Temel Istatistik Eğitim Sağlık ve Sosyal Bilimler için , Prof.Dr.Kazım Özdamar, Nisan Kitabevi

Planned Learning Activities and Teaching Methods

1- To understand the definition and subject of statistics and its relationship with disaster management
2- To explain measures of tendency and measures of variation.
3- To classify variables according to their characterictics
4- To represent and interpret a data set graphically
5- To perform and interpret basic statistical analyses
6- To define fundamental concepts related to the science of statistics.
7- To solve and interpret problems with tos port of programming languages

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 STT TERM WORK (SEMESTER)
3 FCGR FINAL COURSE GRADE
4 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.20 + STT * 0.20 + FN* 0.60
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.20 + STT * 0.20 + RST* 0.60


Further Notes About Assessment Methods

None

Assessment Criteria

to be announced.

Language of Instruction

Turkish

Course Policies and Rules

1- Acquires up-to-date, theoretical, and applied knowledge in the field of statistics.
2- Identifies and solves problems in the field of disaster management using statistical methods.
3- Utilizes analytical thinking skills..
4- Applies computer software and programming knowledge effectively at a level to proficiently use the science of statistics.
5-Collects, analyzes, and interprets data, determining appropriate statistical methods.
6-Identifies statistical problems and develops evidence-based and research-driven solutions.

Contact Details for the Lecturer(s)

Prof.Dr.Istem Köymen-DEÜ IIBF Ekonometri Department

Office Hours

Wednesday-15.30-17.00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Literature review and presentation 14 1
Preparations before/after weekly lectures 14 1
Preparation for midterm exam 1 20
Preparation for final exam 1 20
Midterm 1 1
Final 1 1
TOTAL WORKLOAD (hours) 0

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6
LO.122
LO.2233
LO.3233
LO.423
LO.5333
LO.62
LO.73

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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