Industrial Engineering | |||||
Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 |
Course Code: | FEC201 | ||||||||
Ders İsmi: | Probability and Statistics | ||||||||
Ders Yarıyılı: | Fall | ||||||||
Ders Kredileri: |
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Language of instruction: | Turkish | ||||||||
Ders Koşulu: | |||||||||
Ders İş Deneyimini Gerektiriyor mu?: | No | ||||||||
Type of course: | Required | ||||||||
Course Level: |
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Mode of Delivery: | E-Learning | ||||||||
Course Coordinator : | Asst. Prof. Dr. BAHAR YALÇIN KAVUŞ | ||||||||
Course Lecturer(s): |
Asst. Prof. Dr. BAHAR YALÇIN KAVUŞ |
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Course Assistants: |
Course Objectives: | To learn the basics of probability and statistics and their applications in engineering problems. |
Course Content: | This course provides a comprehensive introduction to probability theory and engineering applications. Among the topics covered in the course; probability definition and rules; random variables and uncertainty, expected value, variance and standard deviation; discrete probability distributions: Bernoulli, Binomial, geometric and Poisson distributions; continuous probability distributions: smooth, exponential and normal distributions; multivariate probability distributions, covariance and correlation; descriptive statistics; sampling and sampling distributions; estimation and confidence interval; Hypothesis tests are simple correlation. |
The students who have succeeded in this course;
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Week | Subject | Related Preparation |
1) | Introduction to Probability. Example Space, simple events and event definitions. Probability axioms | |
2) | Conditional Probability, independent, incompatibilism. Counting techniques, Permutation Combination. Tree Diagram. Binomial and Multiple Binomial Theorems | Lecture Notes |
3) | Random Variable, Expectation (Mean) value, variance and standard deviation | Lecture Notes |
4) | Discrete random variables ( Bernoulli , Binomial, Poisson ) | Lecture Notes |
5) | Continuous random variables (Uniform, Exponential, Gamma, Gaussian) | Lecture Notes |
6) | Distribution functions of Discrete and Continuous random variables | |
7) | Markov and Chebychev inequality. Moment generating functions and their characteristics | Lecture Notes |
8) | Mid term | Lecture Notes |
9) | Marginal and conditional probabilities of two-dimensional probability distribution functions | Lecture Notes |
10) | Independence, covariance, correlation and correlation coefficient of two-dimensional random variables | Lecture Notes |
11) | Law of large numbers, Central limit theorem, hypothesis testing | Lecture Notes |
12) | Normality and single sample tests | Lecture Notes |
13) | Two Sample Test (Dependent and Independent two sample t test) and non -parametric equivalents) | Lecture Notes |
14) | N sample hypothesis tests and non -parametric equivalents | Lecture Notes |
15) | Final | Lecture Notes |
Course Notes / Textbooks: | Leon-Garcia, Alberto (3rd ed.) Probability, statistics, and random processes for electrical engineering |
References: | 1. Leon-Garcia, Alberto (3rd ed.) Probability, statistics, and random processes for electrical engineering 2. Sheldon M. Ross. (Sixth Edition) Introduction to Probability and Statistics for Engineers and Scientists |
Ders Öğrenme Kazanımları | 1 |
4 |
2 |
3 |
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Program Outcomes |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution |
Semester Requirements | Number of Activities | Level of Contribution |
Midterms | 1 | % 50 |
Final | 1 | % 50 |
total | % 100 | |
PERCENTAGE OF SEMESTER WORK | % 50 | |
PERCENTAGE OF FINAL WORK | % 50 | |
total | % 100 |