TR
11111

COURSE INTRODUCTION AND APPLICATION INFORMATION

eco.ieu.edu.tr

Course Name
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
Fall
Prerequisites
None
Course Language
Course Type
Required
Course Level
-
Mode of Delivery -
Teaching Methods and Techniques of the Course
Course Coordinator
Course Lecturer(s)
Assistant(s)
Course Objectives
Learning Outcomes The students who succeeded in this course;
  • will be able to create and use graphs for categorical and numerical data, and to describe relationships between variables
  • will be able to use measures of central tendency, variation, and shape, and use population summary measures
  • will be able to use covariance and correlation to identify relationships between numerical variables
  • will be able to assess outcomes and events in a probability experiment, apply basic rules of probability
  • will be able to apply the concept of statistical independence and use Bayes' Theorem
  • will be able to use mean and standard deviation for discrete and continuous random variables
  • will be able to use and apply some special probability distributions, and the normal approximation to the binomial distribution
  • will be able to use and apply linear combinations of random variables
Course Description

 



Course Category

 Core Courses
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Required Materials
1 Decision making in an uncertain environment. Describing data and summarizing descriptive relationships. Classification of variables. Statistics for Engineers and Scientists, William Navidi, 4th Ed., Mc-Graw Hill. - Applied Statistics and Probability for Engineers, Douglas C. Montgomery & George C. Runger, 5th Ed., John Wiley &Sons, Inc.
2 Graphs to describe categorical variables. Graphs to describe timeseries data. Graphs to describe numerical variables. Data presentation errors. Statistics for Engineers and Scientists, William Navidi, 4th Ed., Mc-Graw Hill. - Applied Statistics and Probability for Engineers, Douglas C. Montgomery & George C. Runger, 5th Ed., John Wiley &Sons, Inc.
3 Measures of central tendency and location. Statistics for Engineers and Scientists, William Navidi, 4th Ed., Mc-Graw Hill. - Applied Statistics and Probability for Engineers, Douglas C. Montgomery & George C. Runger, 5th Ed., John Wiley &Sons, Inc.
4 Measures of variability. Measures of relationships between variables. Statistics for Engineers and Scientists, William Navidi, 4th Ed., Mc-Graw Hill. - Applied Statistics and Probability for Engineers, Douglas C. Montgomery & George C. Runger, 5th Ed., John Wiley &Sons, Inc.
5 Random experiment, outcomes, events. Probability and its postulates. Statistics for Engineers and Scientists, William Navidi, 4th Ed., Mc-Graw Hill. - Applied Statistics and Probability for Engineers, Douglas C. Montgomery & George C. Runger, 5th Ed., John Wiley &Sons, Inc.
6 Probability rules. Statistics for Engineers and Scientists, William Navidi, 4th Ed., Mc-Graw Hill. - Applied Statistics and Probability for Engineers, Douglas C. Montgomery & George C. Runger, 5th Ed., John Wiley &Sons, Inc.
7 Bivariate probabilities. Bayes' Theorem. Statistics for Engineers and Scientists, William Navidi, 4th Ed., Mc-Graw Hill. - Applied Statistics and Probability for Engineers, Douglas C. Montgomery & George C. Runger, 5th Ed., John Wiley &Sons, Inc.
8 Random variables. Probability distributions for discrete random variables. Properties of discrete random variables. Statistics for Engineers and Scientists, William Navidi, 4th Ed., Mc-Graw Hill. - Applied Statistics and Probability for Engineers, Douglas C. Montgomery & George C. Runger, 5th Ed., John Wiley &Sons, Inc.
9 Binomial distribution. Poisson distribution. Statistics for Engineers and Scientists, William Navidi, 4th Ed., Mc-Graw Hill. - Applied Statistics and Probability for Engineers, Douglas C. Montgomery & George C. Runger, 5th Ed., John Wiley &Sons, Inc.
10 Hypergeometric distribution. Jointly distributed discrete random variables. Statistics for Engineers and Scientists, William Navidi, 4th Ed., Mc-Graw Hill. - Applied Statistics and Probability for Engineers, Douglas C. Montgomery & George C. Runger, 5th Ed., John Wiley &Sons, Inc.
11 Linear functions of random variables. Portfolio analysis. Statistics for Engineers and Scientists, William Navidi, 4th Ed., Mc-Graw Hill. - Applied Statistics and Probability for Engineers, Douglas C. Montgomery & George C. Runger, 5th Ed., John Wiley &Sons, Inc.
12 Continuous random variables. Expectations for continuous random variables. Statistics for Engineers and Scientists, William Navidi, 4th Ed., Mc-Graw Hill. - Applied Statistics and Probability for Engineers, Douglas C. Montgomery & George C. Runger, 5th Ed., John Wiley &Sons, Inc.
13 The Normal distribution. Normal distribution approximation. Statistics for Engineers and Scientists, William Navidi, 4th Ed., Mc-Graw Hill. - Applied Statistics and Probability for Engineers, Douglas C. Montgomery & George C. Runger, 5th Ed., John Wiley &Sons, Inc.
14 The exponential distribution. Jointly distributed continuous random variables. Statistics for Engineers and Scientists, William Navidi, 4th Ed., Mc-Graw Hill. - Applied Statistics and Probability for Engineers, Douglas C. Montgomery & George C. Runger, 5th Ed., John Wiley &Sons, Inc.
15 Financial Applications. Statistics for Engineers and Scientists, William Navidi, 4th Ed., Mc-Graw Hill. - Applied Statistics and Probability for Engineers, Douglas C. Montgomery & George C. Runger, 5th Ed., John Wiley &Sons, Inc.
16 Review of the Semester  
Course Notes/Textbooks

Statistics for Engineers and Scientists, William Navidi, 4th Ed., Mc-Graw Hill.
Suggested Readings/Materials Essentials of Contemporary Business statistics by T.A. Williams, D.J. Sweeney, D.R. Anderson,2007, Thomson

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
Laboratory / Application
Field Work
Quizzes / Studio Critiques
4
20
Portfolio
Homework / Assignments
Presentation / Jury
Project
Seminar / Workshop
Oral Exam
Midterm
1
35
Final Exam
1
45
Total

Weighting of Semester Activities on the Final Grade
5
55
Weighting of End-of-Semester Activities on the Final Grade
1
45
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Course Hours
(Including exam week: 16 x total hours)
16
3
48
Laboratory / Application Hours
(Including exam week: 16 x total hours)
16
Study Hours Out of Class
15
2
Field Work
Quizzes / Studio Critiques
3
5
Portfolio
Homework / Assignments
Presentation / Jury
Project
Seminar / Workshop
Oral Exam
Midterms
2
20
Final Exams
1
25
    Total
158

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
 Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1 To have a sound knowledge of the quantitative and qualitative methods that will help to examine the premises of different theories for an applied subject so that a contribution to solving current economic problems can be made. X
2 To have the experience of writing, using software, and doing presentations in the newspapers, magazines, meetings, panels, and in equivalent virtual platforms (internet), in order to share their accumulated knowledge and problem solving ability acquired during their education.
3 To be able to participate in academic, professional, regional, and global networks and to utilize these networks efficiently.
4 To have adequate social responsibility and awareness with regards to the needs of the society and to have sufficient experience and qualifications to organize and support the activities to influence the social dynamics in line with the social goals.
5 To be able to integrate the knowledge and training acquired during the university education with personal and work experience and produce a synthesis of knowledge she requires.
6 To have the ability to evaluate his/her advance (post graduate) level educational needs and do necessary planning to fulfill those needs through the acquired capability to think analytically and critically.
7 To have sufficient practical and theoretical knowledge base in order to define the economic agents and their interaction both in the national and global level, to process economic data and to implement scientific research for development of economic policies.
8 Keeping in mind that economics is a social science, to have the skills to integrate social dynamics into economic process both as an input and an output and to be open to theoretical innovations in this direction.
9 To associate accumulated knowledge acquired during the university education with historical and cultural qualities of the society and to convey it to different groups.
10 To be able to follow knowledge and change in economics and communicate with colleagues in a foreign language.
11 To possess social, scientific and ethical values at the data collection, interpretation and dissemination stages of economic analysis. X
12 To have advanced level of speaking and writing skills of a second foreign language to support continuation of post graduate professional and individual development

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

 

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