MAT3026 Probability and StatisticsBahçeşehir UniversityDegree Programs ELECTRICAL AND ELECTRONICS ENGINEERINGGeneral Information For StudentsDiploma SupplementErasmus Policy StatementNational QualificationsBologna Commission
ELECTRICAL AND ELECTRONICS ENGINEERING
Bachelor TR-NQF-HE: Level 6 QF-EHEA: First Cycle EQF-LLL: Level 6

Course Introduction and Application Information

Course Code Course Name Semester Theoretical Practical Credit ECTS
MAT3026 Probability and Statistics Spring 3 0 3 6

Basic information

Language of instruction: English
Type of course: Must Course
Course Level: Bachelor’s Degree (First Cycle)
Mode of Delivery: Face to face
Course Coordinator : Instructor NERMINE AHMED EL SISSI
Course Lecturer(s): Dr. Öğr. Üyesi MÜRÜVVET ASLI AYDIN
Recommended Optional Program Components: None
Course Objectives: Topics in probability and statistics are introduced through their definitions leading to the development of basic probabilistic and statistical tools. Emphasis is placed on using these tools to solve engineering problems and to make informed decisions.

Learning Outcomes

The students who have succeeded in this course;
1) Calculate probability using permutations and combinations
2) Calculate probability of unions and intersects
3) Determine the reliability block diagram of a system of elements
4) Understand the conditional probability an apply on probability problems
5) Calculate probability using probability distribution functions
6) Calculate expectation values
7) Apply hypothesis testing
8) Determine confidence intervals

Course Content

The course will cover the following topics:
Counting and probability (both theoretical and experimental definitions);
Rules of probability (based on set theory); conditional probability;
The random variable; probability mass functions and density functions;
Expectation values; sampling theory (mean and standard deviation); hypothesis testing;
Confidence intervals (for the population mean, population standard deviation).

Weekly Detailed Course Contents

Week Subject Related Preparation
1) Introduction to the course.
2) Counting and probability.
3) Rules of Probability (sets, additive rules, independence), the Reliability Block Diagram.
4) Conditional probability (independence, Bayes' theory).
5) The random variable, and probability distributions (discrete and continuous) \ review.
6) Expectation values: the population mean.
7) Expectation values: the population standard deviation.
8) Special discrete distributions (Geometric, Hypergeometric, Binomial, Poisson).
9) Special continuous distributions (Exponential, Weibull, Normal).
10) Sampling (the sampled mean and standard deviation, and their distributions) \ review.
11) Hypothesis testing (p-values for the mean and standard deviation, t- and chi-square-distributions).
12) Confidence intervals I - intervals for the mean, pairing, standard error in the sample mean.
13) Confidence intervals II - intervals for the mean (two population)
14) Confidence intervals III - intervals for the standard deviation.

Sources

Course Notes / Textbooks: Walpole, Ronald E., et al. "Probability & Statistics for Engineers & Scientists", Prentice Hall, 9th ed.
References: Douglas C. Montgomery & George C. Runger. "Applied Statistics and Probability for Engineers”; (2011) Wiley.
Devore, Jay.; "Probability & Statistics for Engineering and the Sciences". CengageBrain.com.

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Midterms 2 % 60
Final 1 % 40
Total % 100
PERCENTAGE OF SEMESTER WORK % 60
PERCENTAGE OF FINAL WORK % 40
Total % 100

ECTS / Workload Table

Activities Number of Activities Duration (Hours) Workload
Course Hours 14 3 42
Study Hours Out of Class 14 7 98
Midterms 1 2 2
Final 1 2 2
Total Workload 144

Contribution of Learning Outcomes to Programme Outcomes

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) Adequate knowledge in mathematics, science and electric-electronic engineering subjects; ability to use theoretical and applied information in these areas to model and solve engineering problems. 4
2) Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose. 3
3) Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose. (Realistic constraints and conditions may include factors such as economic and environmental issues, sustainability, manufacturability, ethics, health, safety issues, and social and political issues, according to the nature of the design.) 2
4) Ability to devise, select, and use modern techniques and tools needed for electrical-electronic engineering practice; ability to employ information technologies effectively.
5) Ability to design and conduct experiments, gather data, analyze and interpret results for investigating engineering problems. 4
6) Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
7) Ability to communicate effectively in English and Turkish (if he/she is a Turkish citizen), both orally and in writing.
8) Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.
9) Awareness of professional and ethical responsibility.
10) Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development. 1
11) Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of engineering solutions.