Kocaeli University / European Credit Transfer System (ECTS)

Name of Lecturer(s)

Prof. Dr. Selçuk KOÇ
Associate Prof. Dr. Ozan GÖNÜLLÜ

Learning Outcomes of the Course Unit
Program Competencies-Learning Outcomes Relation

Learning Outcomes of the Course Unit

1) Modeling real business administration problems
2) To learn the numerical methods approaches that can be used to solve business problems
3) To be able to apply numerical methods to solve business problems.
4) To be able to interpret and report the analysis results obtained with the solution of models
5) To make rational decisions by using the results obtained with problem solving

Program Competencies-Learning Outcomes Relation

		Program Competencies
		1	2	3
Learning Outcomes
	1	No relation	High	High
	2	High	High	High
	3	High	High	High
	4	High	High	High
	5	High	High	High

Mode of Delivery

Face to Face

Prerequisites and Co-Requisites

None

Recommended Optional Programme Components

Statistic I

Course Contents

Probability Theory and Probability Distributions, Decision Theory, Utility Theory, Linear Programming, Sensitivity Analysis, Transportation and Assignment Problems, Game Theory, Integer Programming, Goal Programming

Weekly Schedule

1) Data and Statistics: Elements, Variables and Observations; Qualitative and Quantitative Data; Data Sources
2) Descriptive Statistics : Summarizing Quantitative and Qualitative Data in Tabular and Graphical Form
3) Descriptive Statistics: Summarizing Quantitative Data, Crosstabulations and Scatter Diagrams
4) Descriptive Statistics: Measures of Central Tendency (Arithmetic Mean, Trimmed Mean, Weighted Mean, Median, Mode, Quatiles)
5) Descriptive Statistics: Measures of Central Tendency (Arithmetic Mean, Trimmed Mean, Weighted Mean, Median, Mode, Quatiles
6) Descriptive Statistics : Measures of Dispersion (Range, Interquartile Range, Variance, Standard Deviation, Coefficient of Variation)
7) Descriptive Statistics: Uses of Mean and Standard Deviation (Z-scores, Chebyshev's Theorem)
8) Midterm Examination/Assessment
9) Descriptive Statistics: Exploratory Data Analysis, Measures of Association, Covariance and Correlation Coefficient
10) Introduction to Probability
11) Introduction to Probability
12) Discrete Probability Distributions: Random Variables, Expected Value and Variance, Binom and Poisson Probability Distribution
13) Discrete Probability Distributions: Random Variables, Expected Value and Variance, Binom and Poisson Probability Distribution
14) Continuous Probability Distributions: Normal Probability and Exponential Probability Distributions
15) Continuous Probability Distributions: Normal Probability and Exponential Probability Distributions
16) Final Examination

Planned Learning Activities and Teaching Methods

Assessment Methods and Criteria

Contribution of Midterm Examination to Course Grade	30%
Contribution of Final Examination to Course Grade	70%
Total	100%

Language of Instruction

Turkish

Work Placement(s)

Not Required

Course Unit Title	Course Unit Code	Type of Course Unit	Level of Course Unit	Year of Study	Semester	ECTS Credits
Quantitative Methods I	MFD121	Elective	Doctorate degree	1	Fall	6