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SECTION I: GENERAL INFORMATION ABOUT THE COURSE

Course Code Course Name Year Semester Theoretical Practical Credit ECTS
60542TAEOZ-BUS0473 Statistics for Business 2 Fall 3 0 3 5
Course Type : Compulsory
Cycle: Bachelor      TQF-HE:6. Master`s Degree      QF-EHEA:First Cycle      EQF-LLL:6. Master`s Degree
Language of Instruction: English
Prerequisities and Co-requisities: N/A
Mode of Delivery: Face to face
Name of Coordinator: Profesör Dr. OSMAN ZİHNİ ZAİM
Dersin Öğretim Eleman(lar)ı: Dr. Öğr. Üyesi ÖZGÜR BURÇAK GÜRSOY YENİLMEZ
Profesör Dr. OSMAN ZİHNİ ZAİM
Dersin Kategorisi: Field Specific

SECTION II: INTRODUCTION TO THE COURSE

Course Objectives & Content

Course Objectives: This course introduces basic statistical concepts and methods to the students. It aims to give an understanding on what is data and how to apply descriptive and inferential methods to analyze data.
Course Content: Descriptive methods including classification of variables, different graphs and numerical measures, overview of probability theory and probability distributions, confidence interval estimation, hypothesis tests and regression analysis.

Course Learning Outcomes (CLOs)

Course Learning Outcomes (CLOs) are those describing the knowledge, skills and competencies that students are expected to achieve upon successful completion of the course. In this context, Course Learning Outcomes defined for this course unit are as follows:
Knowledge (Described as Theoritical and/or Factual Knowledge.)
  1) Successful students in this course will be able to gather quantitative data and analyze with appropriate techniques.
Skills (Describe as Cognitive and/or Practical Skills.)
  1) Successful students in this course will be able to determine the hypothesis and test them with appropriate techniques.
Competences (Described as "Ability of the learner to apply knowledge and skills autonomously with responsibility", "Learning to learn"," Communication and social" and "Field specific" competences.)
  1) Successful students in this course will have basic skills and ability to independently assess quantitative data.
  2) Successful students in this course will be able to determine the hypothesis and test them with appropriate techniques.
  3) Students successfully terminating this course willbe able to seek rational solutions to researchproblems.
  4) Successful students in this course will be able to present data with proper graphs and measures.

Weekly Course Schedule

Week Subject
Materials Sharing *
Related Preparation Further Study
1) Introduction Darrell Huff, How to Lie with Statistics (1954). Darrell Huff, How to Lie with Statistics (1954).
2) Graphs to Describe Data Newbold et. al. (2013), Chapter 1 Newbold et. al. (2013), Chapter 1
3) Numerical Measures to Describe Data – I Newbold et. al. (2013), Chapter 2; Field, (2016), Chapter 1 Newbold et. al. (2013), Chapter 2; Field, (2016), Chapter 1
4) Numerical Measures to Describe Data – II Newbold et. al. (2013), Chapter 2; Field (2016), Chapter 1 Newbold et. al. (2013), Chapter 2; Field (2016), Chapter 1
5) Weighting and Grouping Data Newbold et. al. (2013), Chapter 2 Newbold et. al. (2013), Chapter 2
6) Probability Methods Newbold et. al. (2013), Chapter 3 Newbold et. al. (2013), Chapter 3
7) Probability Distributions Newbold et. al. (2013), Chapter 4 & 5 Newbold et. al. (2013), Chapter 4 & 5
8) Midterm Exam
9) Sampling Distributions Newbold et. al. (2013), Chapter 6 Newbold et. al. (2013), Chapter 6
10) Confidence Intervals – I Newbold et. al. (2013), Chapter 7 & 8 Newbold et. al. (2013), Chapter 7 & 8
11) Confidence Intervals – II Newbold et. al. (2013), Chapter 7 & 8 Newbold et. al. (2013), Chapter 7 & 8
12) Hypothesis Tests – I Newbold et. al. (2013), Chapter 9 & 10; Field (2016), Chapter 2 Newbold et. al. (2013), Chapter 9 & 10; Field (2016), Chapter 2
13) Hypothesis Tests – II Newbold et. al. (2013), Chapter 9 & 10; Field (2016), Chapter 2 Newbold et. al. (2013), Chapter 9 & 10; Field (2016), Chapter 2
14) Regression Analysis Newbold et. al. (2013), Chapter 11 Newbold et. al. (2013), Chapter 11
*These fields provides students with course materials for their pre- and further study before and after the course delivered.

Recommended or Required Reading & Other Learning Resources/Tools

Course Notes / Textbooks: Paul Newbold, Wiiliam L. Carlson and Betty M. Thorne, Statistics for Business and Economics 8e (Boston: Pearson, 2013).Andy Field, Discovering Statistics Using IBM SPSS Statistics (London: Sage Publications, 2016).
Darrell Huff, How to Lie with Statistics (New York: W. W. Norton & Company, 1954).
References: Paul Newbold, Wiiliam L. Carlson and Betty M. Thorne, Statistics for Business and Economics 8e (Boston: Pearson, 2013).Andy Field, Discovering Statistics Using IBM SPSS Statistics (London: Sage Publications, 2016).
Darrell Huff, How to Lie with Statistics (New York: W. W. Norton & Company, 1954).

SECTION III: RELATIONSHIP BETWEEN COURSE UNIT AND COURSE LEARNING OUTCOMES (CLOs)

(The matrix below shows how the course learning outcomes (CLOs) associates with programme learning outcomes (both KPLOs & SPLOs) and, if exist, the level of quantitative contribution to them.)

Relationship Between CLOs & PLOs

(KPLOs and SPLOs are the abbreviations for Key & Sub- Programme Learning Outcomes, respectively. )
CLOs/PLOs KPLO 1 KPLO 2 KPLO 3 KPLO 4 KPLO 5
1 2 1 1 2 1 2 3 4 1 2 3 4 5 6 7 8 9 10 11 12
CLO1
CLO2
CLO3
CLO4
CLO5
CLO6

Level of Contribution of the Course to PLOs

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Programme Learning Outcomes Contribution Level (from 1 to 5)
1) Learns and uses the basic information, concepts and theories required in the field of international trade.
2) Use information and communication technologies and business applications and international trade in information systems effectively.
3) Can develop effective management strategies using appropriate theory and methods; plan, co-ordinate, implement and control management processes
4) Applies the theoretical knowledge in business life during a semester.
5) S/he acquires the competencies that develop by the expectations of business world and the society defined as the institutional outcomes of our university on the advanced level in relation with his/her field.

SECTION IV: TEACHING-LEARNING & ASSESMENT-EVALUATION METHODS OF THE COURSE

Teaching & Learning Methods of the Course

(All teaching and learning methods used at the university are managed systematically. Upon proposals of the programme units, they are assessed by the relevant academic boards and, if found appropriate, they are included among the university list. Programmes, then, choose the appropriate methods in line with their programme design from this list. Likewise, appropriate methods to be used for the course units can be chosen among those defined for the programme.)
Teaching and Learning Methods defined at the Programme Level
Teaching and Learning Methods Defined for the Course
Lectures
Discussion
Case Study
Problem Solving
Demonstration
Views
Laboratory
Reading
Homework
Project Preparation
Thesis Preparation
Peer Education
Seminar
Technical Visit
Course Conference
Brain Storming
Questions Answers
Individual and Group Work
Role Playing-Animation-Improvisation
Active Participation in Class

Assessment & Evaluation Methods of the Course

(All assessment and evaluation methods used at the university are managed systematically. Upon proposals of the programme units, they are assessed by the relevant academic boards and, if found appropriate, they are included among the university list. Programmes, then, choose the appropriate methods in line with their programme design from this list. Likewise, appropriate methods to be used for the course units can be chosen among those defined for the programme.)
Aassessment and evaluation Methods defined at the Programme Level
Assessment and Evaluation Methods defined for the Course
Midterm
Presentation
Final Exam
Quiz
Report Evaluation
Homework Evaluation
Oral Exam
Thesis Defense
Jury Evaluation
Practice Exam
Evaluation of Implementation Training in the Workplace
Active Participation in Class
Participation in Discussions

Relationship Between CLOs & Teaching-Learning, Assesment-Evaluation Methods of the Course

(The matrix below shows the teaching-learning and assessment-evaluation methods designated for the course unit in relation to the course learning outcomes.)
LEARNING & TEACHING METHODS
COURSE LEARNING OUTCOMES
ASSESMENT & EVALUATION METHODS
CLO1 CLO2 CLO3 CLO4 CLO5 CLO6
-Lectures -Midterm
-Discussion -Presentation
-Case Study -Final Exam
-Problem Solving -Quiz
-Demonstration -Report Evaluation
-Views -Homework Evaluation
-Laboratory -Oral Exam
-Reading -Thesis Defense
-Homework -Jury Evaluation
-Project Preparation -Practice Exam
-Thesis Preparation -Evaluation of Implementation Training in the Workplace
-Peer Education -Active Participation in Class
-Seminar - Participation in Discussions
-Technical Visit
-Course Conference
-Brain Storming
-Questions Answers
-Individual and Group Work
-Role Playing-Animation-Improvisation
-Active Participation in Class

Contribution of Assesment & Evalution Activities to Final Grade of the Course

Measurement and Evaluation Methods # of practice per semester Level of Contribution
Homework Assignments 3 % 15.00
Midterms 1 % 35.00
Semester Final Exam 1 % 50.00
Total % 100
PERCENTAGE OF SEMESTER WORK % 50
PERCENTAGE OF FINAL WORK % 50
Total % 100

SECTION V: WORKLOAD & ECTS CREDITS ALLOCATED FOR THE COURSE

WORKLOAD OF TEACHING & LEARNING ACTIVITIES
Teaching & Learning Activities # of Activities per semester Duration (hour) Total Workload
Course 14 3 42
Laboratory 0 0 0
Application 0 0 0
Special Course Internship (Work Placement) 0 0 0
Field Work 0 0 0
Study Hours Out of Class 0 0 0
Presentations / Seminar 0 0 0
Project 0 0 0
Homework Assignments 0 0 0
Total Workload of Teaching & Learning Activities - - 42
WORKLOAD OF ASSESMENT & EVALUATION ACTIVITIES
Assesment & Evaluation Activities # of Activities per semester Duration (hour) Total Workload
Quizzes 2 15 30
Midterms 1 20 20
Semester Final Exam 1 40 40
Total Workload of Assesment & Evaluation Activities - - 90
TOTAL WORKLOAD (Teaching & Learning + Assesment & Evaluation Activities) 132
ECTS CREDITS OF THE COURSE (Total Workload/25.5 h) 5