COURSE UNIT TITLE

: RESEARCH METHODS AND SPSS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
ISY 7037 RESEARCH METHODS AND SPSS COMPULSORY 3 0 0 10

Offered By

Management Science Non-Thesis (Evening)

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR ALI ÖZDEMIR

Offered to

Management Science Non-Thesis (Evening)
Quantitative Methods Non-thesis (Evening)

Course Objective

This course aims to
Ensure the students be able to use the scientific research methods based on analitic thinking to solve the problems be faced about business administration.
Gain the students data collection, modelling, data analysis, reporting skills to solve the business problems in the scientifical research methods process.

Learning Outcomes of the Course Unit

1   Able to detect business problems and to name this problems in accordance with a research topic.
2   Able to make literature review about research topic
3   Able to determine the variables about research topic
4   Able to model and solve real problems about corresponding business functions
5   Able to hypothesize about research problems
6   Able to collect data about research topic and analyse these data by package programs with statistical and mathematical methods
7   Able to interpret and report analyse findings and results with scientific basis.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Scientific Research, Core Concepts in Research Methodologies, Types of Research, Tools of Research
2 Adopting Research topic, Defining research s Problem Statement, Stating Aims and importance of the Research, The Research Proposal, Literature Review
3 Determining the Research Variables and Hypothesis, Creating Research Model
4 Measuring and Scaling in Researches
5 Error Resources in Measuring and Measuring Errors, Validity and Reliability in Scales
6 Determining the population and the sample, determination of sample size and sample error
7 Data and Data Resources, Primary Data Collection Methods Comparing Means, Parametric Hypothesis Tests
8 Managing data and data organizing menus in SPSS
9 Statistical data analysis, Descriptive Statistics Analysis, Frequency Analysis
10 Comparing Means, Parametric Hypothesis Tests
11 Linear Regression and Correlation Analysis, Logistic Regression Analysis
12 Factor Analysis Reliability Analysis, Nonparametric Tests
13 Evaluating Research Findings, Writing and presentation of research report
14 Evaluating Research Findings, Writing and presentation of research report

Recomended or Required Reading

Yönetim Biliminde Ileri Araştırma Yöntemleri ve Uygulamalar, Doç.Dr. Ali.ÖZDEMIR, Beta Basım Yayım Dağıtım A.Ş., Istanbul, 2010
Supplementary Book(s):
All books and academic journals about research methodologies

Planned Learning Activities and Teaching Methods

Lectures, Class Discussions, Questions-Answers, Homework Presentations and Sample Applications

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 STT TERM WORK (SEMESTER)
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.30 + STT * 0.30 + FIN* 0.40
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + STT * 0.30 + RST* 0.40


Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

Turkish

Course Policies and Rules

Attending at least 70 percent of lectures is mandatory.
It s expected to obey scientific research rules and ethics in the preparation of homework presentations
It s expected that to support the homework presentations with business applications and package program analysis.

Contact Details for the Lecturer(s)

Doç.Dr. Ali Özdemir
Dokuz Eylül Üniversitesi Iktisadi ve Idari Bilimler FAkültesi Işletme Bölümü Sayısal Yöntemler Anabilim Dalı
Office No: 332 Tel: (232)3010612 e-mail: ali.ozdemir@deu.edu.tr
Personal Web: http://kisi.deu.edu.tr/ali.ozdemir

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparations before/after weekly lectures 14 3 42
Preparation for midterm exam 1 15 15
Preparation for final exam 1 25 25
Preparing assignments 3 30 90
Preparing presentations 3 6 18
Midterm 1 4 4
Final 1 4 4
TOTAL WORKLOAD (hours) 240

Contribution of Learning Outcomes to Programme Outcomes

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