ARTIFICIAL INTELLIGENCE ENGINEERING | |||||
Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 |
Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
MAT3026 | Probability and Statistics | Fall | 3 | 0 | 3 | 6 |
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. |
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 |
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). |
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. |
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. |
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 |
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 |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution | |
1) | Have sufficient background in mathematics, science and artificial intelligence engineering. | 5 |
2) | Use theoretical and applied knowledge in the fields of mathematics, science and artificial intelligence engineering together for engineering solutions. | 5 |
3) | Identify, define, formulate and solve engineering problems, select and apply appropriate analytical methods and modeling techniques for this purpose. | |
4) | Analyse a system, system component or process and design it under realistic constraints to meet desired requirements; apply modern design methods in this direction. | |
5) | Select and use modern techniques and tools necessary for engineering applications. | |
6) | Design and conduct experiments, collect data, and analyse and interpret results. | |
7) | Work effectively both as an individual and as a multi-disciplinary team member. | |
8) | Access information via conducting literature research, using databases and other resources | |
9) | Follow the developments in science and technology and constantly update themself with an awareness of the necessity of lifelong learning. | |
10) | Use information and communication technologies together with computer software with at least the European Computer License Advanced Level required by their field. | |
11) | Communicate effectively, both verbal and written; know a foreign language at least at the European Language Portfolio B1 General Level. | |
12) | Have an awareness of the universal and social impacts of engineering solutions and applications; know about entrepreneurship and innovation; and have an awareness of the problems of the age. | |
13) | Have a sense of professional and ethical responsibility. | |
14) | Have an awareness of project management, workplace practices, employee health, environment and work safety; know the legal consequences of engineering practices. |