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Information
| Code | BBZ205 |
| Name | Probability and Statistics |
| Term | 2024-2025 Academic Year |
| Semester | 3. Semester |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Belirsiz |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. GÜZİN YÜKSEL |
| Course Instructor |
Prof. Dr. GÜZİN YÜKSEL
(A Group)
(Ins. in Charge)
|
Course Goal / Objective
This course aims to lay the foundation for an introduction to statistics by teaching information about probability theory, random variables and the distributions of these variables.
Course Content
Random experiment, sample space, event, probability function, probability calculations, conditional probability, random variables, functions of random variables, discrete random variables and their distributions.
Course Precondition
There are no prerequisites.
Resources
Olasılık ve İstatistik, Fikri Akdeniz, Nobel Yayınevi Olasılık ve İstatistik, Semra Oral Erbaş, Gazi Kitabevi.
Notes
Olasılığa Giriş, George Roussas, Çeviri Editörü: Prof. Dr. Şanslı Şenol, Doç. Dr. Güzin Yüksel.
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Understands sample spaces, sample points and counting sample points rules. |
| LO02 | Uses frequency table in analysis |
| LO03 | Uses measures of central tendency and dispersion |
| LO04 | Apply the rules of conditional probability |
| LO05 | Understands the concept of a random variable and distribution of a random variable |
| LO06 | Recognize the expected value, variance and properties of a random variable. |
| LO07 | Uses the concepts of regression and correlation |
| LO08 | Recognizes discrete and continuous distributions |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Gain comprehensive knowledge of fundamental concepts, algorithms, and data structures in Computer Science. | |
| PLO02 | Bilgi - Kuramsal, Olgusal | Learn essential computer topics such as software development, programming languages, and database management | |
| PLO03 | Bilgi - Kuramsal, Olgusal | Understand advanced computer fields like data science, artificial intelligence, and machine learning. | 4 |
| PLO04 | Bilgi - Kuramsal, Olgusal | Acquire knowledge of topics like computer networks, cybersecurity, and database design. | |
| PLO05 | Beceriler - Bilişsel, Uygulamalı | Develop skills in designing, implementing, and analyzing algorithms | |
| PLO06 | Beceriler - Bilişsel, Uygulamalı | Gain proficiency in using various programming languages effectively | |
| PLO07 | Beceriler - Bilişsel, Uygulamalı | Learn skills in data analysis, database management, and processing large datasets. | 5 |
| PLO08 | Beceriler - Bilişsel, Uygulamalı | Acquire practical experience through working on software development projects. | |
| PLO09 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Strengthen teamwork and communication skills. | 3 |
| PLO10 | Yetkinlikler - Alana Özgü Yetkinlik | Foster a mindset open to technological innovations. | |
| PLO11 | Yetkinlikler - Öğrenme Yetkinliği | Encourage the capacity for continuous learning and self-improvement. | |
| PLO12 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Enhance the ability to solve complex problems | 4 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Sample spaces, sample points, counting rules for sample points | Reading source | Öğretim Yöntemleri: Beyin Fırtınası, Anlatım |
| 2 | Independent Events, Complete independence, Conditional Probability and Bayes' Theorem | Reading source | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 3 | Organising Data (frequency table) and Graphs | Reading source | Öğretim Yöntemleri: Anlatım, Tartışma, Soru-Cevap |
| 4 | Mean, Mod, Median, Standard Deviation and Other Central Tendency and Dispersion Measures | Reading source | Öğretim Yöntemleri: Anlatım, Tartışma |
| 5 | Discrete and continous random variables, Expected Value, Variance, Moments, Moment Generating Functions | Reading source | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 6 | Discrete probability distributions | Reading source | Öğretim Yöntemleri: Anlatım, Tartışma, Soru-Cevap |
| 7 | Continous probability distributions | Reading source | Öğretim Yöntemleri: Soru-Cevap, Anlatım, Tartışma |
| 8 | Mid-Term Exam | Review of topics discussed in the lecture notes and sources | Ölçme Yöntemleri: Yazılı Sınav |
| 9 | Probability Distribution with two random variables, marginal and conditional probability distributions | Reading source | Öğretim Yöntemleri: Soru-Cevap, Anlatım |
| 10 | Point estimate, interval estimate, confidence intervals | Reading source | Öğretim Yöntemleri: Anlatım, Tartışma |
| 11 | Hyphoteses Testing (Error Types, critical values, decision making, testing means, testing ratios, testing differences between two means, variance test) | Reading source | Öğretim Yöntemleri: Soru-Cevap, Anlatım |
| 12 | Tests for goodness of fit, test of independence and test of homogeneity | Reading source | Öğretim Yöntemleri: Anlatım, Tartışma |
| 13 | Simple Regression and Correlation | Reading source | Öğretim Yöntemleri: Anlatım, Tartışma |
| 14 | Least squares method, parameter estimates, coefficient of determination | Reading source | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 15 | Review and Examples | Review of topics discussed in the lecture notes and sources | Öğretim Yöntemleri: Alıştırma ve Uygulama, Soru-Cevap |
| 16 | Term Exams | Review of topics discussed in the lecture notes and sources | Ölçme Yöntemleri: Yazılı Sınav |
| 17 | Term Exams | Review of topics discussed in the lecture notes and sources | Ölçme Yöntemleri: Yazılı Sınav |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 6 | 84 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 8 | 8 |
| Final Exam | 1 | 16 | 16 |
| Total Workload (Hour) | 150 | ||
| Total Workload / 25 (h) | 6,00 | ||
| ECTS | 6 ECTS | ||