COURSE UNIT TITLE

: DATA ANALYSIS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
DBA 6383 DATA ANALYSIS COMPULSORY 3 0 0 6

Offered By

Business Administration (English)

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

PROFESSOR DOCTOR AYSUN KAPUÇUGIL IKIZ

Offered to

Business Administration (English)

Course Objective

The objective of this course is to provide students with the essentials and computational methods of statistical data analysis, and to give various application examples in business.

Learning Outcomes of the Course Unit

1   Have a knowledge understanding of the use of basic and advanced tools of statistics.
2   Demonstrate their skills and knowledge to analyze real data by using the appropriate techniques and software with a high level of confidence.
3   Perform a complete statistical data analysis and develop solutions to realistic cases and apply their skills in interpreting computer output.
4   Have experience writing a report using the language of modern statistics to communicate the results and explain the managerial implication.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to Statistics: General Framework of Statistical World Lecture
2 Displaying and Summarizing Data Computer Applications -Lab Exercises
3 Probability Concepts and Distributions Lecture
4 Sampling Distributions: the Central Limit Theorem Lecture
5 Inferential Statistics: Estimation Computer Applications -Lab Exercises
6 Inferential Statistics: Hypothesis Testing Computer Applications -Lab Exercises
7 Comparison Two or More Populations, Analysis of Variance Computer Applications -Lab Exercises
8 Correlation and Regression Analysis Computer Applications -Lab Exercises
9 Regression- Additional Topics and Model Building Computer Applications -Lab Exercises
10 Time Series Analysis Computer Applications -Lab Exercises
11 Qualitative Data Analysis Computer Applications -Lab Exercises
12 Categoric Data Analysis, Nonparametric Methods Computer Applications -Lab Exercises
13 Comprehensive Case Analysis
14 Comprehensive Case Analysis

Recomended or Required Reading

Text Books:
* Statistics for Business and Economics. Paul Newbold, W. L. Carlson and B. Thorne, 7th Ed. or later Ed., Prentice-Hall.
* Statistical Techniques in Business and Economics. Lind, D.A., Marchal, W.G. and Wathen, S.A., 15th ed, 2012, McGraw-Hill.
* Statistics, Data Analysis, and Decision Modeling. James R. Evans, 4th ed. or later, 2010, Pearson Education.

Software:
* Minitab
* IBM SPSS
* MS Excel

Planned Learning Activities and Teaching Methods

1. Lectures
2. Review Sessions and Class Discussions
3. Computer Applications
4. Case Analysis

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


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

1. Grade for Student Participation will depend on (i) class attendance, (ii) the quality of the answers student provide to questions posed by the instructor during class, and (iii) the general contribution the student make to the creation of a positive learning environment.
2. A good attendance record will bring the grade up one level, for grades on the boundary between two grade levels.
3. The case analysis requires a systematic and analytic thinking to integrate all business functions and formulate strategies that will enable businesses to succeed in the business environment. It is the responsibility of the student to contribute to class discussions actively. The contribution will be evaluated for such factors as apparent understanding of the topic, originality and clarity of discussion, comprehensiveness of the solution strategy formulated.

Language of Instruction

English

Course Policies and Rules

1. It is obligatory to attend at least 70% of the classes.
2. Violations of Plagiarism of any kind will result in disciplinary steps being taken.
3. Absence will not be considered an excuse for submitting homework assignments late.
4. Delayed case reports will suffer grade decay equivalent to one letter grade per day late.

Contact Details for the Lecturer(s)

Prof.Dr. Aysun KAPUÇUGIL IKIZ
aysun.kapucugil@deu.edu.tr

DEU Faculty of Business
Department of Business Administration
Division of Quantitative Methods

Office Hours

To be announced later

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparations before/after weekly lectures 12 3 36
Preparation for midterm exam 1 15 15
Preparation for final exam 1 15 15
Preparing assignments 8 5 40
Midterm 1 3 3
Final 1 3 3
TOTAL WORKLOAD (hours) 154

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5
LO.15553
LO.255
LO.3355
LO.455555