ECTS - Probability and Statistics I
Probability and Statistics I (MATH291) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Probability and Statistics I | MATH291 | Area Elective | 3 | 0 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| N/A |
| Course Language | English |
|---|---|
| Course Type | Elective Courses |
| Course Level | Bachelor’s Degree (First Cycle) |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture, Question and Answer, Problem Solving. |
| Course Lecturer(s) |
|
| Course Objectives | In addition to some tools for classification, summarization and making sense of data, to provide students with basic probability knowledge and certain probability distributions |
| Course Learning Outcomes |
The students who succeeded in this course;
|
| Course Content | Basic definitions, tables and graphs, central tendency measures, central dispersion measures, probability concept, conditional probability, Bayesian approach, random variables, expected value, binomial and normal distributions. |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | Basic Definitions, Frequency Distributions | pp. 3-5 |
| 2 | Relative, Cumulative, Cumulative Relative Frequency Distributions, Graphs, Stem and Leaf Display | pp. 24-28 |
| 3 | Central Tendency Measures; Mean, Median and Mode for Unclassified and Classified Data | pp. 73-76 |
| 4 | Central Dispersion Measures; Variance, Standard Deviation, Coefficient of Variation, Chebyshev Theorem | pp. 93-100 |
| 5 | Probability Concept, Random Event-Experiment, Sample Space, | pp. 127-130 |
| 6 | Classical / Postrerior Probability Definitions , Rule of Counting; Permutation and Combination, Multiplication Rule | pp. 135-137 |
| 7 | Midterm Exam | |
| 8 | Venn Diagrams, Contingency Table, Conditional Probability | pp. 138-140 |
| 9 | Bayesian Approach, Statistical Indpendency | pp. 142-145 |
| 10 | Random Variables, Probability Function | pp. 147-150 |
| 11 | Expected Value and Its Properties, Mean and Standard Deviation | pp. 155-157 |
| 12 | Binomial Distribution | pp. 167-168 |
| 13 | Normal Distribution, Standard Normal Variable, Z table | pp. 182-185 |
| 14 | Problems on Normal Distribution and Vice-Verse Usage of Z table (Cut-off value ) | pp. 199-205 |
| 15 | Review | |
| 16 | Final Exam |
Sources
| Course Book | 1. D.H. Sanders, R. K. Simidt, Statistics, A First Course, 1990 |
|---|---|
| Other Sources | 2. D.H. Sanders, R. K. Simidt, Statistics, A First Course, 1990 |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | - | - |
| Laboratory | - | - |
| Application | - | - |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | - | - |
| Homework Assignments | 2 | 10 |
| Presentation | - | - |
| Project | - | - |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 2 | 50 |
| Final Exam/Final Jury | 1 | 40 |
| Toplam | 5 | 100 |
| Percentage of Semester Work | 60 |
|---|---|
| Percentage of Final Work | 40 |
| Total | 100 |
Course Category
| Core Courses | X |
|---|---|
| Major Area Courses | |
| Supportive Courses | |
| Media and Managment Skills Courses | |
| Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
| # | Program Qualifications / Competencies | Level of Contribution | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | Obtain adequate knowledge in mathematics, science and subjects specific to the Materials Engineering; the ability to apply theoretical and practical knowledge of these areas to solve complex engineering problems and to model and solve of materials systems | X | ||||
| 2 | Obtain understanding of science and engineering principles related to the structures, properties, processing and performance of Materials systems | |||||
| 3 | Obtain the ability to identify, define, formulate and solve complex engineering problems; selecting and applying proper analysis and modeling techniques for this purpose | X | ||||
| 4 | Obtain the ability to design and choose proper materials for a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design and materials selection methods for this purpose | X | ||||
| 5 | Obtain the ability to develop, select and utilize modern techniques and tools essential for the analysis and solution of complex problems in Materails Engineering applications; the ability to utilize information technologies effectively | X | ||||
| 6 | Obtain the ability to design and conduct experiments, collect data, analyse and interpret results using statistical and computational methods for complex engineering problems or research topics specific to Materials Engineering | X | ||||
| 7 | Obtain the ability to work effectively in inter/inner disciplinary teams; ability to work individually | |||||
| 8 | Obtain effective oral and written communication skills in Turkish; knowlegde of at least one foreign language; the ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions | |||||
| 9 | Obtain recognition of the need for lifelong learning; the ability to access information; follow recent developments in science and technology with continuous self-development | |||||
| 10 | Obtain the ability to behave according to ethical principles, awareness of professional and ethical responsibility; knowledge of standards used in engineering applications | |||||
| 11 | Obtain knowledge on business practices such as project management, risk management and change management; awareness in entrepreneurship and innovativeness; knowledge of sustainable development | |||||
| 12 | Obtain knowledge of the effects of Materials Engineering applications on the universal and social dimensions of health, environment and safety, knowledge of modern age problems reflected on engineering; awareness of legal consequences of engineering solutions | |||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| Course Hours (Including Exam Week: 16 x Total Hours) | |||
| Laboratory | |||
| Application | |||
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | 14 | 3 | 42 |
| Presentation/Seminar Prepration | |||
| Project | |||
| Report | |||
| Homework Assignments | |||
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 2 | 10 | 20 |
| Prepration of Final Exams/Final Jury | 1 | 15 | 15 |
| Total Workload | 77 | ||