COURSE UNIT TITLE

: STATISTICS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
MBA 5078 STATISTICS COMPULSORY 3 0 0 3

Offered By

Business Administration (English)

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSISTANT PROFESSOR BANU DEMIREL

Offered to

Business Administration (English)

Course Objective

Aim of the course is to provide students with the necessary foundation in creating a competent research methodology, collecting data, analyzing the data, interpreting and communicating the results for research problems. The course illustrates the integration between statistics and research methods by demonstrating the ways to use statistics in analyzing data collected during research. In this course, the focus will be mostly on the methodology aspect of research design and the usage of advanced statistical concepts and techniques.

Learning Outcomes of the Course Unit

1   Design an appropriate research by using the quantitative and qualitative methods relevant to satisfactorily address a particular research question.
2   Collect data using a variety of methods.
3   Identify and interpret patterns in data
4   Perform a complete statistical analysis and develop solutions to real problems and apply their skills in interpreting computer output.
5   Be able to organize statistics and present them graphically and verbally so that a nontechnical audience can understand them
6   Have experience writing a report to evaluate the research and communicate the results.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Types of Research Study: Quantitative and Qualitative Research
2 Data Collection Methods: Collecting Primary Data (Survey Research - Focus Groups - Interviewing)
3 Preliminary Examination of the Data; Revisiting Inferential Statistics Reliability and Validity
4 Bivariate Measures of Association
5 The logic of Experimental Design Experimental Designs with more than two levels of an Independent Variable
6 Complex Experimental Designs Quasi-Experimental and Single-Case Designs
7 Analysis of Variance/ Manova / Mancova / Ancova
8 Midterm
9 Using Secondary Data; Exploring Data Patterns
10 Multiple Regression Analysis
11 Forecasting with Time Series Models and Multiple Regression, Judgmental Forecasting
12 Writing and presenting a research report
13 Research project presentations
14 Research project presentations

Recomended or Required Reading

Research Methods for Business Students. Mark Saunders, Philip Lewis, Adrian Thornhill (2012). Pearson Education. 6th Edition.
Statistics for Business and Economics. Paul Newbold, W. L. Carlson and B. Thorne, 7th Ed. or later Ed., Prentice-Hall.
Multivariate Data Analysis. Joseph F. Hair, William C. Black, Barry J. Babin and Rolph E. Anderson, 7th Edition, 2009, Pearson Education.
Research Methods and Statistics: A Critical Thinking Approach, Sherri L.Jackson, (2012). Wadsworth - Cengage Learning, 4th edition.
Other course materials are also drawn from a range of textbooks and journal articles.
4. Software:
Minitab / SPSS ® (Statistical Package for Social Sciences)

Planned Learning Activities and Teaching Methods

The course consists of lectures, class discussions, computer applications, assignments and projects.

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

Lectures will focus on the transfer of research designs and advanced statistical concepts and techniques where comprehension is substantially enhanced by additional elaboration and illustration.
Exams will measure the ability to identify and apply the appropriate method to the real situations. Each exam will cover course materials and include exercises like those assigned for homework, questions on lecture materials, and additional items covered in class meetings.
Students are required to complete an individual Research Project which allows them to apply the concepts and skills they have developed to a topic of personal or professional interest. Each week as making progress through the text and new techniques are introduced, the students will apply these new skills to their research project. By the end of the term, students will have completed a rather sophisticated research as reported in professional journals and in popular media.
By completing the research project, students will improve analytical and communication skills through identifying and applying the relevant research and statistical methodology to the real problems. Research reports will enable students improve their competency using the language of statistics to communicate the results.
Research Project reports will be graded by the instructors and be evaluated for such factors as apparent understanding of the topic, originality of treatment and discussion, accuracy of results, comprehensiveness of the report s content and depth of the analysis, clarity and mechanics of presentation such as organization, format, punctuation, grammar, and quality of exhibits and charts.
Grade for Student Participation will depend on (i) class attendance, (ii) the quality of answers the student provides to questions posed by the instructor during class, and (iii) the general contribution the student makes to the creation of a positive learning environment.
A good attendance record may bring the grade up one level, for grades on the boundary between two grade levels.

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 research projects will suffer grade decay equivalent to one letter grade per day late.

Contact Details for the Lecturer(s)

aysun.kapucugil@deu.edu.tr
Room no: 126/A
Office tel: 232.3018286

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 12 3 36
Preparations before/after weekly lectures 10 1 10
Preparation for midterm exam 1 8 8
Preparation for final exam 1 8 8
Web Search and Library Research 3 2 6
Preparing assignments 5 2 10
Preparing presentations 1 3 3
Final 1 1,5 2
Midterm 1 1,5 2
TOTAL WORKLOAD (hours) 85

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8
LO.13555
LO.2355
LO.3555
LO.4555
LO.555
LO.655