COURSE UNIT TITLE

Offered By

Faculty Of Business

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR ERDOST TORUN

Offered to

Political Science and International Relations (English)
Economics (English)
International Business and Trade (English)
Tourism Management (English)
International Trade and Business (English)
International Relations (English)
BUSINESS ADMINISTRATION (English)

Course Objective

The course aims to provide students the basic descriptive and inferential statistical techniques for solving administrative and social sciences -oriented problems.

Learning Outcomes of the Course Unit

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Recomended or Required Reading

1. Text Books:
Statistics for Business and Economics by P. Newbold, W. L. Carlson and B. Thorne, 7th Ed. or later Ed., Prentice-Hall.
Statistical Techniques in Business and Economics by Douglas A. Lind, William G. Marchal and Samuel A. Wathen, 15th Edition, McGraw-Hill/Irwin.
2. Software (subject to the departmental needs):
Spreadsheet Software with Data Analysis add-in.
SPSS ® (Statistical Package for Social Sciences)
3. Calculator:
Students will need a scientific calculator for various calculation problems in and out of class, and during exams.

Planned Learning Activities and Teaching Methods

1. Lectures
Class lecture is highly interactive and format is direct. The instructor prompts students for response to questions posed and solicits their thoughts on issues discussed. Lectures will focus on the transfer of basic statistical concepts and techniques where comprehension is substantially enhanced by additional elaboration and illustration. The emphasis is on real world applications rather than rigorous mathematics.

2. Review Sessions and Class Discussions
Review sessions will be handled by the instructor each week in the last session of a lecture. In-class assignments and homework assignments are the basis of problems to be solved in these sessions. Individual participation by students in classroom discussion will be strongly encouraged.

3. Computer Applications
In the laboratory component, a data analysis add-in tool and/or a particular statistical package will be introduced to perform analyses of data. Instruction on the use of the software as it relates to statistical problems will be provided in class and in the book.

Assessment Methods

Further Notes About Assessment Methods

1. Midterm and Final Exams
Exams will measure the ability to identify and apply the appropriate statistic and/or method to real world problems. Each exam will cover course materials and include problems like those assigned for homework, questions on lecture materials, and additional items covered in class meetings.

Assessment Criteria

In exams, there will be one major part for each chapter. In each part, one or more questions are asked. Depending upon the general performance level of the students and the instructor's own initiative, the bell-curve calculations might be used to transform the grades. If any exam question is left unanswered, the value of that question will be subtracted from the exam score. If only the answer is given (i.e., no work showing how that answer was determined), the question will be graded at 25% of its value.

Language of Instruction

English

Course Policies and Rules

1. Attending at least 70 percent of lectures is mandatory.
2. Plagiarism of any type will result in disciplinary action.
3. Absence will not be considered an excuse for submitting homework assignments late.
4. Students are required to have their own calculator for this course. It will not be allowed to share a calculator during exams. Cellular phones cannot be used as a calculator during an exam.

Contact Details for the Lecturer(s)

Asst.Prof.Dr.Güzin Özdağoğlu
Asst.Prof.Dr.Aysun Kapucugil Ikiz
Asst.Prof.Dr.Fırat Özdemir
Asst.Prof.Dr.Sedat Çapar
Dr. Joshua David Cowley

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Contribution of Learning Outcomes to Programme Outcomes