Undergraduate
Faculty of Economic and Administrative Sciences
Economics
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Economics Main Page / Program Curriculum / Probability and Statistics I

Probability and Statistics I

Course CodeSemester Course Name LE/RC/LA Course Type Language of Instruction ECTS
IKT3005 3 Probability and Statistics I 2/2/0 CC Turkish 5
Course Goals
Statistics as a discipline provides a wide variety of methods to assist in data analysis and decision making. Descriptive statistics focus on the collection, summarization and characterization of set of data,Inferential statistics estimate a characteristic of a set of data.

In general, business managers need to be knowledgeable abouth statistics in order to understand how
properly present and desciribe information

Draw conclusion abouth large populations based only on information obtained from sample

Improve process

Obtain reliable forcasts
Prerequisite(s) None
Corequisite(s) None
Special Requisite(s) None
Instructor(s) Assoc. Prof. Nebile Korucu Gümüşoğlu, Arş. Gör. Çağıl Kaya Çamalan
Course Assistant(s)
Schedule Monday 09:00 - 10:50 BK Z-02 Wednesday 15:00 - 16:50 BK L-02
Office Hour(s) Nebile Korucu Gümüşoğlu B Block Floor 7 Çağıl Kaya Çamalan B Block Floor 8
Teaching Methods and Techniques Lectures, computer lab, power-point presentations
Principle Sources Statistics for Business and Economics , Newbold P.,Carlson W., Thorne B., 2006

Business Statistics, Levine, Berenson,2002

Durmuş Dündar, Nazan Çağlar, İstatistik, Der Yayınevi- 2008

Statistics for Business & Economics, Paul Newbold,W.Carlson , 2002
Other Sources  Case studies and lecture notes to be given by the lecturer are among the other resources
Course Schedules
Week Contents Learning Methods
1. Week Why a Manager needs to know about statistics ,Why Data are needed? Sources of data , Types of data Lectures, computer lab., power-point presentations
2. Week Organizing numerical data, Tables and charts for numerical and categorical data, Using Microsoft Excel for Tables and Charts Lectures, computer lab., power-point presentations
3. Week The Mean , Median , Mod and other measures of central tendency Lectures, computer lab., power-point presentations
4. Week The Standart Deviation and other measures of dispersion, Using Microsoft Excel For Descriptive Statistics Lectures, computer lab., power-point presentations
5. Week Probability and its Postulates,exercises Lectures, computer lab., power-point presentations
6. Week Bayes’ Theorem , Probability distributions Lectures, computer lab., power-point presentations
7. Week Discrete Random Variables, Binomal Distribution Lectures, computer lab., power-point presentations
8. Week Poisson Distribution, Continuous Random Variables and Normal Distribution Lectures, computer lab., power-point presentations
9. Week Midterm Week Assessment
10. Week Midterm Week Assessment
11. Week Normal Distribution and applications, Sampling Theory Lectures, computer lab., power-point presentations
12. Week Exercises Lectures, computer lab., power-point presentations
13. Week Confidence Interval, Exercises Lectures, computer lab., power-point presentations
14. Week Exercises Lectures, computer lab., power-point presentations
15. Week Final Exam Week Assessment
16. Week Final Exam Week Assessment
17. Week Final Exam Week Assessment
Assessments
Evaluation tools Quantity Weight(%)
Midterm(s) 1 40
Quizzes 1 10
Final Exam 1 50


Program Outcomes
PO-1To define his/her competencies using the theoretical and practical knowledge he/she acquired in the field of Economics and to use these competencies in practice.
PO-2To discuss concepts and ideas in the field of Economics with scientific methods, to develop hypotheses, to interpret and evaluate the data obtained.
PO-3To develop solution suggestions for complex and/or unpredictable problems encountered in practice, to report and present these suggestions in accordance with the academic publication rules.
PO-4To identify regional and global issues/problems, to perform analyses based on scientific data and research, and to develop solution suggestions.
PO-5To determine the learning needs in the field of Economics, to evaluate the acquired knowledge and skills with a critical approach, and to use this knowledge and skills to develop economic policies.
PO-6To inform relevant people and institutions on issues related to the field of Economics and to gain the ability to convey written and verbal solutions to problems.
PO-7To convey his/her thoughts and suggestions in the field of Economics to experts and non-experts by supporting them with quantitative and qualitative data, to discuss and to contribute to the development of new policies by revising suggestions according to the feedback he/she receives.
PO-8To benefit from other disciplines that form the basis of the field of Economics, to develop multidisciplinary approaches by associating these disciplines with his/her knowledge in the field of Economics, to produce project and publications.
PO-9To define the differences and relationships between classical and modern theories of economics and to observe the distinctions between classical and modern economic policies and to evaluate the compatibility of these policies with economic and social issues.
PO-10To read and comprehend foreing news sources about economics being fluent in a foreign language, to scan the economic literature and to follow the most current approaches in this field.
PO-11To take into account scientific and ethical values in the stages of collecting, interpreting and announcing economic data and carrying out statistical/econometric studies using these data, and also to carry out the publication process in accordance with academic publishing principles.
Learning Outcomes
LO-1Gain application skills of solving business problems
LO-2Research, practice and determine how to use the field analysis on theoretical and practical knowledge and skills gained in the field of business administration
LO-3Use of statistical tools in making forward-looking estimates
LO-4Able to obtain a good statistical knowledge of technical analysis
LO-5Being an accoutred systems analyst
Course Assessment Matrix:
Program Outcomes - Learning Outcomes Matrix
 PO 1PO 2PO 3PO 4PO 5PO 6PO 7PO 8PO 9PO 10PO 11
LO 1
LO 2
LO 3
LO 4
LO 5