BST153 Inferential StatisticsIstanbul Okan UniversityDegree Programs Automotive Engineering (English)General Information For StudentsDiploma SupplementErasmus Policy StatementNational Qualifications
Automotive Engineering (English)
Bachelor TR-NQF-HE: Level 6 QF-EHEA: First Cycle EQF-LLL: Level 6

General course introduction information

Course Code: BST153
Course Name: Inferential Statistics
Course Semester: Spring
Course Credits:
Theoretical Practical Credit ECTS
3 0 3 6
Language of instruction: TR
Course Requisites:
Does the Course Require Work Experience?: No
Type of course: University Elective
Course Level:
Bachelor TR-NQF-HE:6. Master`s Degree QF-EHEA:First Cycle EQF-LLL:6. Master`s Degree
Mode of Delivery: Face to face
Course Coordinator : Dr.Öğr.Üyesi FERİDUN CEMAL ÖZÇAKIR
Course Lecturer(s):
Course Assistants:

Course Objective and Content

Course Objectives: The aim of this course is to teach students how to estimate population parameters from sample values and how to test hypotheses about these parameters.
Course Content: In this course, Sampling Methods, Central Limit Theorem in Random Sampling, Estimation of Population Mean, Estimation of Population Ratio Estimation, Estimation of Population Variance, Parametric Hypothesis Tests, Tests and Stages of Hypothesis, Tests of Mean, Tests of Proportion, Tests of Variance, Between Two and More than Two Population Mean Tests of Difference – Analysis of Variance – F Test are explained.

Learning Outcomes

The students who have succeeded in this course;
Learning Outcomes
1 - Knowledge
Theoretical - Conceptual
1) Students will be able to estimate population parameters from sample values.
2 - Skills
Cognitive - Practical
1) Students will be able to test hypotheses about population parameters.
3 - Competences
Communication and Social Competence
Learning Competence
Field Specific Competence
Competence to Work Independently and Take Responsibility

Lesson Plan

Week Subject Related Preparation
1) Sampling Methods
2) Central Limit Theorem in Random Sampling
3) Estimation of Population Mean
4) Estimation of Population Ratio Estimation
5) Estimation of Population Variance
6) Parametric Hypothesis Tests
7) Tests and Stages of Hypothesis
8) Midterm
9) Tests of Mean, Tests of Proportion
10) Tests of Proportion
11) Tests of Variance
12) Between Two and More than Two Population Mean Tests of Difference
13) Analysis of Variance
14) F Test

Sources

Course Notes / Textbooks: Çözümsel İstatistik - Prof. Dr. Nuray Girginer
References: Çözümsel İstatistik - Prof. Dr. Nuray Girginer

Course-Program Learning Outcome Relationship

Learning Outcomes

1

2

Program Outcomes
1) Sufficient knowledge in mathematics, science and engineering related to their branches; and the ability to apply theoretical and practical knowledge in these areas to model and solve engineering problems.
2) The ability to identify, formulate, and solve complex engineering problems; selecting and applying appropriate analysis and modeling methods for this purpose.
3) The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design methods for this purpose. (Realistic constraints and conditions include such issues as economy, environmental issues, sustainability, manufacturability, ethics, health, safety, social and political issues, according to the nature of design.)
4) Ability to develop, select and use modern techniques and tools necessary for engineering applications; ability to use information technologies effectively.
5) Ability to design experiments, conduct experiments, collect data, analyze and interpret results to examine engineering problems or discipline-specific research topics.
6) The ability to work effectively in disciplinary and multidisciplinary teams; individual work skill.
7) Effective communication skills in Turkish oral and written communication; at least one foreign language knowledge; ability to write effective reports and understand written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions.
8) Awareness of the need for lifelong learning; access to knowledge, ability to follow developments in science and technology, and constant self-renewal.
9) Conform to ethical principles, and standards of professional and ethical responsibility; be informed about the standards used in engineering applications.
10) Awareness of applications in business, such as project management, risk management and change management; awareness of entrepreneurship, and innovation; information about sustainable development.
11) Information about the universal and social health, environmental and safety effects of engineering applications and the ways in which contemporary problems are reflected in the engineering field; awareness of the legal consequences of engineering solutions.
12) Knowledge on advanced calculus, including differential equations applicable to automotive engineering; familiarity with statistics and linear algebra; knowledge on chemistry, calculus-based physics, dynamics, structural mechanics, structure and properties of materials, fluid dynamics, heat transfer, manufacturing processes, electronics and control, design of vehicle elements, vehicle dynamics, vehicle power train systems, automotive related regulations and vehicle validation/verification tests; ability to integrate and apply this knowledge to solve multidisciplinary automotive problems; ability to apply theoretical, experimental and simulation methods and, computer aided design techniques in the field of automotive engineering; ability to work in the field of vehicle design and manufacturing.

Course - Learning Outcome Relationship

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) Sufficient knowledge in mathematics, science and engineering related to their branches; and the ability to apply theoretical and practical knowledge in these areas to model and solve engineering problems.
2) The ability to identify, formulate, and solve complex engineering problems; selecting and applying appropriate analysis and modeling methods for this purpose.
3) The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design methods for this purpose. (Realistic constraints and conditions include such issues as economy, environmental issues, sustainability, manufacturability, ethics, health, safety, social and political issues, according to the nature of design.)
4) Ability to develop, select and use modern techniques and tools necessary for engineering applications; ability to use information technologies effectively.
5) Ability to design experiments, conduct experiments, collect data, analyze and interpret results to examine engineering problems or discipline-specific research topics.
6) The ability to work effectively in disciplinary and multidisciplinary teams; individual work skill.
7) Effective communication skills in Turkish oral and written communication; at least one foreign language knowledge; ability to write effective reports and understand written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions.
8) Awareness of the need for lifelong learning; access to knowledge, ability to follow developments in science and technology, and constant self-renewal.
9) Conform to ethical principles, and standards of professional and ethical responsibility; be informed about the standards used in engineering applications.
10) Awareness of applications in business, such as project management, risk management and change management; awareness of entrepreneurship, and innovation; information about sustainable development.
11) Information about the universal and social health, environmental and safety effects of engineering applications and the ways in which contemporary problems are reflected in the engineering field; awareness of the legal consequences of engineering solutions.
12) Knowledge on advanced calculus, including differential equations applicable to automotive engineering; familiarity with statistics and linear algebra; knowledge on chemistry, calculus-based physics, dynamics, structural mechanics, structure and properties of materials, fluid dynamics, heat transfer, manufacturing processes, electronics and control, design of vehicle elements, vehicle dynamics, vehicle power train systems, automotive related regulations and vehicle validation/verification tests; ability to integrate and apply this knowledge to solve multidisciplinary automotive problems; ability to apply theoretical, experimental and simulation methods and, computer aided design techniques in the field of automotive engineering; ability to work in the field of vehicle design and manufacturing.

Learning Activity and Teaching Methods

Expression
Individual study and homework
Lesson

Assessment & Grading Methods and Criteria

Written Exam (Open-ended questions, multiple choice, true-false, matching, fill in the blanks, sequencing)
Homework

Assessment & Grading

Semester Requirements Number of Activities Level of Contribution
Midterms 1 % 40
Final 1 % 60
total % 100
PERCENTAGE OF SEMESTER WORK % 40
PERCENTAGE OF FINAL WORK % 60
total % 100

Workload and ECTS Credit Grading

Activities Number of Activities Duration (Hours) Workload
Course Hours 14 42 588
Homework Assignments 3 9 27
Midterms 1 1 1
Final 1 1 1
Total Workload 617