Psychology | |||||
Bachelor | Length of the Programme: 4 | Number of Credits: 240 | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF: Level 6 |
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 |
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 |