TOROS ÜNİVERSİTESİ
Bilgi Paketi Ders Kataloğu

Course Information

NUMERICAL METHODS
Code	Semester	Theoretical	Practice	National Credit	ECTS Credit
		Hour / Week
MAN306	Spring	3	0	3	5

Prerequisites and co-requisites	None
Language of instruction	English
Type	Required
Level of Course	Bachelor's
Lecturer	Assist.Prof.Dr. Kenan ORÇANLI
Mode of Delivery	Face to Face
Suggested Subject	None
Professional practise ( internship )	None
Objectives of the Course	To provide an introduction to some concepts of probability theory and statistics, and also decision theory and multi criteria decision making with applications of enterprises problems.
Contents of the Course	Permutations, Combinatins, Probability, Discrete and Continuous random variables with their probability distributions and expectations, Samping distributions.

Learning Outcomes of Course

#	Learning Outcomes
1	will be able to define knowledge about sets.
2	will be able to define knowledge about probability theory.
3	will be able to apply probability distributions.
4	will be able to define decision theory and utility.
5	will be able to define linear programming models.
6	will be able to define data envelopment analysis.
7	will be able to define analytical hierarchic prosess.
8	will be able to define basics of project management.

Course Syllabus

#	Subjects	Teaching Methods and Technics
1	Body of Knowledge, Problem Solving and Decision Making, Quantitative Analysis and Decision Making	Synchronous (lms.toros.edu.tr)
2	Quantitative Analysis Models of Cost, Revenue, and Profit Quantitative Methods in Practice and Modelling	Synchronous (lms.toros.edu.tr)
3	Linear Programming Problem Problem Formulation, Maximization Problem, Graphical Solution Procedure	Synchronous (lms.toros.edu.tr)
4	Slack and Surplus Variables, Computer Solutions with Excel and GAMS	Synchronous (lms.toros.edu.tr)
5	Linear Programming Problem Problem Formulation, Minimization Problem, Graphical Solution Procedure	Synchronous (lms.toros.edu.tr)
6	Examples with Minimization / Minimization Problems and Computer Solutions with Excel and GAMS	Synchronous (lms.toros.edu.tr)
7	Introduction to Sensitivity Analysis	Synchronous (lms.toros.edu.tr)
8	Mid-Term Exam.	Written exam
9	Right-Hand Sides, Shadow Price, Relevant Cost and Sunk Cost, Range of Feasibility	Synchronous (lms.toros.edu.tr)
10	Simultaneous Changes, Changes in Constraint Coefficients	Synchronous (lms.toros.edu.tr)
11	Marketing Applications, Financial Applications, Operations Management Applications	Synchronous (lms.toros.edu.tr)
12	Marketing Applications, Financial Applications, Operations Management Applications	Synchronous (lms.toros.edu.tr)
13	Decision Analysis (Problem Formulatıon, Decısıon Makıng Wıthout Probabılıtıes, Decısıon Makıng Wıth Probabılıtıes)	Synchronous (lms.toros.edu.tr)
14	Decision Analysis (Rısk Analysıs and Sensıtıvıty Analysıs, Decısıon Analysıs wıth Sample Informatıon, Computıng Branch Probabılıtıes wıth Bayes’ Theorem, Utılıty Theory)	Synchronous (lms.toros.edu.tr)
15	Scorıng Models and Analytıc Hıerarchy Process	Synchronous (lms.toros.edu.tr)
16	Final Exam	Written exam

Course Syllabus

#	Material / Resources	Information About Resources	Reference / Recommended Resources
1	An Introduction to Management Science:Quantitative Approaches to Decision Making, , Fourteenth Edition David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J. Cochran, Michael J. Fry, Jeffrey W. Ohlmann
2	Practical Management Science, 6th Edition Wayne L. Winston and S. Christian Albright

Method of Assessment

#	Weight	Work Type	Work Title
1	40%	Mid-Term Exam	Mid-Term Exam
2	60%	Final Exam	Final Exam

Relationship between Learning Outcomes of Course and Program Outcomes

#	Learning Outcomes	Program Outcomes	Method of Assessment
1	will be able to define knowledge about sets.	3͵4͵7	1͵2
2	will be able to define knowledge about probability theory.	3͵4͵7	1͵2
3	will be able to apply probability distributions.	3͵4͵7	1͵2
4	will be able to define decision theory and utility.	3͵4͵7	1͵2
5	will be able to define linear programming models.	3͵4͵7	1͵2
6	will be able to define data envelopment analysis.	3͵4͵7	1͵2
7	will be able to define analytical hierarchic prosess.	3͵4͵7	1͵2
8	will be able to define basics of project management.	3͵4͵7	1͵2

PS. The numbers, which are shown in the column Method of Assessment, presents the methods shown in the previous table, titled as Method of Assessment.

Work Load Details

#	Type of Work	Quantity	Time (Hour)	Work Load
1	Course Duration	14	3	42
2	Course Duration Except Class (Preliminary Study, Enhancement)	14	3	42
3	Presentation and Seminar Preparation	0	0	0
4	Web Research, Library and Archival Work	0	0	0
5	Document/Information Listing	0	0	0
6	Workshop	0	0	0
7	Preparation for Midterm Exam	1	16	16
8	Midterm Exam	1	2	2
9	Quiz	0	0	0
10	Homework	2	9	18
11	Midterm Project	0	0	0
12	Midterm Exercise	0	0	0
13	Final Project	0	0	0
14	Final Exercise	0	0	0
15	Preparation for Final Exam	1	27	27
16	Final Exam	1	3	3
				150