SECTION I: GENERAL INFORMATION ABOUT THE COURSE

Course Code	Course Name	Year	Semester	Theoretical	Practical	Credit	ECTS
60542TAEOZ-MTH3174	Statistics for Engineering	2	Spring	2	2	3	6

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:	Doçent Dr. NEVZAT EVRİM ÖNAL
Dersin Öğretim Eleman(lar)ı:	Doçent Dr. NEVZAT EVRİM ÖNAL
Dersin Kategorisi:	Field Specific

SECTION II: INTRODUCTION TO THE COURSE

Course Objectives & Content

Course Objectives:

The aim of this lesson is to teach the students the basis of statistical methods, endow them with a theoretical basis for deliberation through statistical tools and concepts and teach them how to employ and assess the results of the most widely used methods of data analysis in the field of engineering.

Course Content:

Introduction to statistics; Population and sample, sample average and variation; Stem and leaf diagram, histogram, box graph, normal probability graph; Sampling; Sample distributions and point estimate of parameters; Statistical intervals for a single sample; Hypothesis tests for a single sample; Statistical inference for two samples; Simple linear regression. This course employs the project-based learning approach. In this respect aside from the conventional content the course has a project-based learning component. The project based- learning component aims realising one or more projects designed for learning purposes involving the development of certain intermediary and final deliverables in a step-by-step mannerby the students individually or in project teams. The evaluation of the project-based learning component involves grading the project deliverables and the project works by the instructor and/or a jury.

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) Understand the fundamental concepts of statistics, use methods of data collection and data measurement.

Skills (Describe as Cognitive and/or Practical Skills.)

1) Present data with tables and figures.

2) Apply exploratory data analysis methods and handle business world applications.

3) Utilize descriptive data analysis tools, compute average and variation, interpret the distribution of data.

4) Calculate simple regressions.

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.)

Weekly Course Schedule

Week	Subject	Materials Sharing *
		Related Preparation	Further Study
1)	Introduction to statistics.	Reading assignment, Preparatory study	Project work, Homework assignment
2)	Assignment of projects	Reading assignment, Preparatory study	Project work, Homework assignment
3)	Population and sample, sample average and variation	Reading assignment, Preparatory study	Project work, Homework assignment
4)	Stem and leaf diagram, histogram, box graph, normal probability graph	Reading assignment, Preparatory study	Project work, Homework assignment
5)	Sampling	Reading assignment, Preparatory study	Project work, Homework assignment
6)	Sample distributions and point estimate of parameters	Reading assignment, Preparatory study	Project work, Homework assignment
7)	Submission of the first delivery of the project	Reading assignment, Preparatory study	Project work, Homework assignment
8)	Midterm	Reading assignment, Preparatory study	Project work, Homework assignment
9)	Statistical intervals for a single sample	Reading assignment, Preparatory study	Project work, Homework assignment
10)	Hypothesis tests for a single sample	Reading assignment, Preparatory study	Project work, Homework assignment
11)	Statistical inference for two samples	Reading assignment, Preparatory study	Project work, Homework assignment
12)	Submission of the first delivery of the project	Reading assignment, Preparatory study	Project work, Homework assignment
13)	Simple linear regression	Reading assignment, Preparatory study	Project work, Homework assignment
14)	Simple linear regression	Reading assignment, Preparatory study	Project work, Homework assignment
15)	Submission of the final delivery of the project and presentation	Reading assignment, Preparatory study	Project work, Homework assignment

*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:	Jay L. Devore, Probability and Statistics for Engineering and the Sciences, Cengage Learning
References:	Paul Newbold, Statistics for Business and Economics, Prentice Hall. Rick Durett, Probability: Theory and Examples, Cambridge University Press Dimitri P. Bertsekas, Introduction to Probability, Athena Scientific David Freedman, Statistics, W.W. Norton & Company

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	1	2	3	4	5	1	2	3	4	5	6	7	8	9	1	2	3	4	1	2	3	4	5	6	7	8	9	10	11	12
CLO1
CLO2
CLO3
CLO4
CLO5

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)	Uses and applies theoretical and applied sciences in the field of basic science subjects for the solution of management engineering problems.	4
	1.1 Has sufficient knowledge in mathematics, science and management engineering; use theoretical and applied knowledge in these fields together to solve Management Engineering problems	4
2)	Analyzes Management Engineering applications, designs and develops models to meet specific requirements under realistic constraints and conditions. For this purpose, it selects and uses appropriate methods, tools and technologies.	4
	2.1 Identifies, defines, formulates and solves complex Management Engineering problems; for this purpose selects and applies appropriate analytical and modeling methods	4
	2.2 Designs a complex system, process, device or product to meet certain requirements under realistic constraints and conditions; applies modern design methods for this purpose	4
	2.3 Selects and uses modern techniques and tools required for engineering applications; uses information technologies and at least one computer software (European Computer Driving License Advanced Level) effectively
	2.4 Designs experiments, conducts experiments, collects data, analyzes and interprets the results for the investigation of engineering problems
	2.5 Designs, develops, implements integrated systems for the production of concrete or abstract outputs containing people, materials, information, equipment and energy; controls and improves the operation of these systems	5
3)	Owns the competencies required by the constantly developing field of management engineering and the global competitive environment.	1
	3.1 Works effectively individually and in multi-disciplinary teams, takes responsibility	1
	3.2 Accesses information and for this purpose searches for resources, uses databases and other information resources
	3.3 Has awareness of the necessity of lifelong learning, follows developments in science and technology and renews itself continuously	2
	3.4 Communicates effectively in Turkish, both orally and in writing, has at least one foreign language knowledge at the level of European Language Portfolio B1	3
	3.5 Manages projects, has conscious of workplace practices, employee health, environmental and work safety; aware of the legal consequences of engineering applications
	3.6 Has awareness of the universal and social effects of engineering solutions and applications; has awareness of entrepreneurship and innovativeness and knowledgeable about contemporary issues	2
	3.7 Has professional and ethical responsibility	2
	3.8 Has consciousness of the concept of quality
	3.9 Has entrepreneurship awareness to undertake the establishment process of a business
4)	Applies the theoretical knowledge in business life during a semester.
	4.1 Experiences all processes in business life.
	4.2 Takes part in activities related to the field of education in a business operating in the field.
	4.3 Questions the application with theoretical knowledge.
	4.4 Compiles the knowledge and experience gained in the field.
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.
	5.1 Acquires the analyzing solving the problems and managing the conflicts.
	5.2 Participates as a team member and takes responsibility in the environments that require the solving of the conflicts and acts as a leader when necessary.
	5.3 Has awareness for ethical and social responsivity.
	5.4 By supporting the learnt courses with quantitative and qualitative data; and by using verbal and visual communication means, s/he transfers them to the groups within and outside his/her group in a systematical and effective way.
	5.5 Evaluates the norms and standards present in the works in which s/he takes responsibility in a critical point of view.
	5.6 Develops strategical, innovative and entrepreneurial ideas.
	5.7 Acquires competence of managing the change.
	5.8 Shows development personally and socially with and awareness for lifelong learning.
	5.9 Follows advanced technologies and developments about digital transformation.
	5.10 Has cultural awareness and s/he transfers this to the groups within and outside his/her field.
	5.11 Has awareness about citizenship competency.
	5.12 Acquires communication in a Foreign Language (English) competence defined on the level of at least B1 in European Language Portfolio. (In programs whose medium of instruction is English, on the level of B2/B2+).

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.)

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

Measurement and Evaluation Methods	# of practice per semester	Level of Contribution
Quizzes	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	4	15	60
Midterms	1	20	20
Semester Final Exam	1	30	30
Total Workload of Assesment & Evaluation Activities	-	-	110
TOTAL WORKLOAD (Teaching & Learning + Assesment & Evaluation Activities)			152
ECTS CREDITS OF THE COURSE (Total Workload/25.5 h)			6