| School/Faculty/Institute | Faculty of Engineering | ||||
| Course Code | MATH 224 | ||||
| Course Title in English | Probability and Statistics for Engineering | ||||
| Course Title in Turkish | Mühendislik için Olasılık ve İstatistik | ||||
| Language of Instruction | EN | ||||
| Type of Course | Flipped Classroom | ||||
| Level of Course | Introductory | ||||
| Semester | Spring,Fall | ||||
| Contact Hours per Week |
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| Estimated Student Workload | 162 hours per semester | ||||
| Number of Credits | 6 ECTS | ||||
| Grading Mode | Standard Letter Grade | ||||
| Pre-requisites | None | ||||
| Expected Prior Knowledge | Prior knowledge in calculus is expected | ||||
| Co-requisites | None | ||||
| Registration Restrictions | Only Undergraduate Students | ||||
| Overall Educational Objective | To learn the fundamentals of probability and statistics and their applications in engineering problems. | ||||
| Course Description | This course provides a comprehensive introduction to probability theory and its applications to engineering. The following topics are covered: definition and rules of probability; random variables and uncertainty, expected value, variance and standard deviation of a probability distribution; discrete probability distributions: the Bernoulli, Binomial, geometric and Poisson distributions; continuous probability distributions: the uniform, exponential and normal distributions; multivariate probability distributions, covariance and correlation; descriptive statistics; sampling and sampling distributions; estimation and confidence interval; hypothesis testing; simple regression. | ||||
| Course Description in Turkish | Bu derste olasılık kuramına ve mühendislik uygulamalarına kapsamlı bir giriş sağlanmaktadır. Derste işlenen konular arasında; olasılık tanımı ve kuralları; rassal değişkenler ve belirsizlik, beklenen değer, varyans ve standart sapma; ayrık olasılık dağılımları: Bernoulli, Binom, geometrik ve Poisson dağılımları; sürekli olasılık dağılımları: düzgün, üstsel ve normal dağılımlar; çok-değişkenli olasılık dağılımları, kovaryans ve korelasyon; betimleyici istatistikler; örnekleme ve örnekleme dağılımları; kestirim ve güven aralığı; hipotez testleri, basit bağlanım bulunmaktadır. |
Course Learning Outcomes and CompetencesUpon successful completion of the course, the learner is expected to be able to:1) Describe fundamentals of probability and statistics; 2) Analyze discrete and continuous probability distributions; 3) Apply statistical methods to solve engineering problems. |
| Program Learning Outcomes/Course Learning Outcomes | 1 | 2 | 3 |
|---|---|---|---|
| 1) Thorough knowledge of the major concepts, theoretical perspectives, empirical findings, and historical trends in psychology. | |||
| 2) Understanding of and ability to apply essential research methods in psychology, including research design, data analysis, and data interpretation. | |||
| 3) Competence to use critical and creative thinking, skeptical inquiry and a scientific approach to solving problems related to behavior and mental processes. | |||
| 4) Understanding and ability to apply psychological principles, skills and values in personal, social, and organizational contexts. | |||
| 5) Ability to weigh evidence, to tolerate ambiguity, and to reflect other values that underpin psychology as a discipline. | |||
| 6) Internalization and dissemination of professional ethical standards. | |||
| 7) Demonstration of competence in information technologies, and the ability to use computer and other technologies for purposes related to the pursuit of knowledge in psychology and the broader social sciences. | |||
| 8) Skills to communicate the knowledge of psychological science effectively, in a variety of formats, in both Turkish and in English (in English, at least CEFR B2 level). | |||
| 9) Recognition, understanding, and respect for the complexity of sociocultural and international diversity. | |||
| 10) Recognition for the need for, and the skills to pursue, lifelong learning, inquiry, and self-improvement. | |||
| 11) Ability to formulate critical hypotheses based on psychological theory and literature, and design studies to test those hypotheses. | |||
| 12) Ability to acquire knowledge independently, and to plan one’s own learning. | |||
| 13) Demonstration of advanced competence in the clarity and composition of written work and presentations. |
| N None | S Supportive | H Highly Related |
| Program Outcomes and Competences | Level | Assessed by | |
| 1) | Thorough knowledge of the major concepts, theoretical perspectives, empirical findings, and historical trends in psychology. | N | |
| 2) | Understanding of and ability to apply essential research methods in psychology, including research design, data analysis, and data interpretation. | N | |
| 3) | Competence to use critical and creative thinking, skeptical inquiry and a scientific approach to solving problems related to behavior and mental processes. | H | Exam,HW,Participation |
| 4) | Understanding and ability to apply psychological principles, skills and values in personal, social, and organizational contexts. | N | |
| 5) | Ability to weigh evidence, to tolerate ambiguity, and to reflect other values that underpin psychology as a discipline. | N | |
| 6) | Internalization and dissemination of professional ethical standards. | N | |
| 7) | Demonstration of competence in information technologies, and the ability to use computer and other technologies for purposes related to the pursuit of knowledge in psychology and the broader social sciences. | N | |
| 8) | Skills to communicate the knowledge of psychological science effectively, in a variety of formats, in both Turkish and in English (in English, at least CEFR B2 level). | N | |
| 9) | Recognition, understanding, and respect for the complexity of sociocultural and international diversity. | S | Participation |
| 10) | Recognition for the need for, and the skills to pursue, lifelong learning, inquiry, and self-improvement. | S | HW,Participation |
| 11) | Ability to formulate critical hypotheses based on psychological theory and literature, and design studies to test those hypotheses. | N | |
| 12) | Ability to acquire knowledge independently, and to plan one’s own learning. | S | Exam,HW |
| 13) | Demonstration of advanced competence in the clarity and composition of written work and presentations. | H | Exam,HW |
| Prepared by and Date | YANİ SKARLATOS , December 2020 |
| Course Coordinator | MEHMET FEVZİ ÜNAL |
| Semester | Spring,Fall |
| Name of Instructor | Prof. Dr. YANİ SKARLATOS |
| Week | Subject |
| 1) | Definition and rules of probability |
| 2) | Definition and rules of probability |
| 3) | Fundamentals of random variables |
| 4) | Discrete probability distributions |
| 5) | Discrete probability distributions |
| 6) | Continuous probability distributions |
| 7) | Continuous probability distributions |
| 8) | Multivariate probability distributions |
| 9) | Multivariate probability distributions |
| 10) | Statistics, sampling and sampling distributions |
| 11) | Estimation |
| 12) | Hypothesis Testing |
| 13) | Hypothesis Testing |
| 14) | Simple regression |
| 15) | Final/Project/Presentation Period |
| 16) | Final/Project/Presentation Period |
| Required/Recommended Readings | Required: Probability and Statistics for Engineers and Scientists; R. E. Walpole,R. H. Myers, S. L. Myers, K. Ye; Pearson, 9th Edition, 2016 Recommended: Probability and Statistics for Engineers; R. L. Scheaffer, J.T. McClave; Duxbury Press, 5th Edition, 2010 | |||||||||||||||
| Teaching Methods | Lectures/contact hours using “flipped classroom” as an active learning technique | |||||||||||||||
| Homework and Projects | None | |||||||||||||||
| Laboratory Work | None | |||||||||||||||
| Computer Use | Yok | |||||||||||||||
| Other Activities | Yok | |||||||||||||||
| Assessment Methods |
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| Course Administration |
skarlatosy@mef.edu.tr Instructor’s office: 5th Floor Office hours: Mon. 12:00-13:00. E-mail address: skarlatosy@mef.edu.tr Rules for attendance: Classroom practice contributes to 14% of the final grade. Missing a midterm: Provided that proper documents of excuse are presented, each missed midterm by the student will be given the grade of the final exam. No make-up will be given. Missing a final: Faculty regulations. A reminder of proper classroom behavior, code of student conduct: YÖK Regulations Academic dishonesty and plagiarism: YÖK Regulations |
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| Activity | No/Weeks | Hours | Calculation | ||||
| No/Weeks per Semester | Preparing for the Activity | Spent in the Activity Itself | Completing the Activity Requirements | ||||
| Course Hours | 14 | 1 | 3 | 1 | 70 | ||
| Quiz(zes) | 12 | 1 | 1 | 24 | |||
| Midterm(s) | 2 | 32 | 2 | 68 | |||
| Total Workload | 162 | ||||||
| Total Workload/25 | 6.5 | ||||||
| ECTS | 6 | ||||||