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
Lecture: 4 Recitation: Lab: None Other: None
Estimated Student Workload 162 hours per semester
Number of Credits 6 ECTS
Grading Mode Standard Letter Grade
Pre-requisites None
Co-requisites None
Expected Prior Knowledge Prior knowledge in calculus is expected
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 Learning Outcomes and Competences

Upon 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) An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics
2) An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors
3) An ability to communicate effectively with a range of audiences
4) An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts
5) An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives
6) An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions
7) An ability to acquire and apply new knowledge as needed, using appropriate learning strategies

Relation to Program Outcomes and Competences

N None S Supportive H Highly Related
     
Program Outcomes and Competences Level Assessed by
1) An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics H Exam,Participation
2) An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors N
3) An ability to communicate effectively with a range of audiences N
4) An ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts N
5) An ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives N
6) An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions N
7) An ability to acquire and apply new knowledge as needed, using appropriate learning strategies H Exam,Participation
Prepared by and Date YANİ SKARLATOS , December 2020
Course Coordinator MEHMET FEVZİ ÜNAL
Semester Spring,Fall
Name of Instructor Prof. Dr. YANİ SKARLATOS

Course Contents

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 ReadingsRequired: 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 MethodsLectures/contact hours using “flipped classroom” as an active learning technique
Homework and ProjectsNone
Laboratory WorkNone
Computer UseYok
Other ActivitiesYok
Assessment Methods
Assessment Tools Count Weight
Application 14 % 14
Quiz(zes) 5 % 20
Midterm(s) 2 % 66
TOTAL % 100
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

ECTS Student Workload Estimation

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