| Semester | Course Unit Code | Course Unit Title | T+P+L | Credit | Number of ECTS Credits | Last Updated Date |
| 3 | EEM 209 | Probability Theory & Statistical Analysis | 4+0+0 | 4 | 7 | 24.08.2022 |
|
Language of Instruction
|
English
|
|
Level of Course Unit
|
Bachelor's Degree
|
|
Department / Program
|
Electrical and Electronics Engineering
|
|
Type of Program
|
Formal Education
|
|
Type of Course Unit
|
Compulsory
|
|
Course Delivery Method
|
Face To Face
|
|
Objectives of the Course
|
Introducing Fundementals of Probability and Statistics and the Necessary Background
|
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Course Content
|
Definition, history, advancement and basic principles of statistics and probability. Statistical methods. Students will be able to analyze the data obtained in their own fields and to obtain correct and meaningful results.
|
|
Course Methods and Techniques
|
|
|
Prerequisites and co-requisities
|
None
|
|
Course Coordinator
|
Associate Prof.Dr. Ümit Deniz ULUŞAR
|
|
Name of Lecturers
|
Prof.Dr. ÜMİT DENİZ ULUŞAR
|
|
Assistants
|
None
|
|
Work Placement(s)
|
No
|
Recommended or Required Reading
|
Resources
|
Matlab Help Files
Engineering Statistics
|
Course Category
|
Mathematics and Basic Sciences
|
%50
|
|
|
Engineering
|
%50
|
|
|
Engineering Design
|
%0
|
|
|
Social Sciences
|
%0
|
|
|
Education
|
%0
|
|
|
Science
|
%0
|
|
|
Health
|
%0
|
|
|
Field
|
%0
|
|
|
Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"
Assessment Methods and Criteria
|
In-Term Studies
|
|
Mid-terms
|
1
|
%
35
|
|
Assignment
|
4
|
%
2,5
|
|
Project
|
1
|
%
10
|
|
Final examination
|
1
|
%
45
|
|
Total
|
7
|
%
92,5
|
ECTS Allocated Based on Student Workload
|
Activities
|
Total Work Load
|
|
Course Duration
|
15
|
1
|
15
|
|
Hours for off-the-c.r.stud
|
15
|
5
|
75
|
|
Assignments
|
4
|
2
|
8
|
|
Mid-terms
|
1
|
3
|
3
|
|
Project
|
1
|
3
|
3
|
|
Final examination
|
1
|
3
|
3
|
|
Total Work Load
| |
|
Number of ECTS Credits 4
107
|
Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
| No | Learning Outcomes |
|
1
| Recognize the basic concepts of statistics and usage methods |
|
2
| Will be able to perform statistical analysis using Matlab and other 3rd party tools. |
|
3
| Will gain research notion |
|
4
| Improve analystical problem solving capabilities |
Weekly Detailed Course Contents
| Week | Topics | Study Materials | Materials |
| 1 |
Introduction
|
|
|
| 2 |
Introduction to Statistics, Basics and Definitions
|
|
|
| 3 |
Measurement Data Variable and Relationship, Classification of Data (Quantitative, Qualitative)
|
|
|
| 4 |
Descriptive Statistics, Measuring Central Tendency
|
|
|
| 5 |
Graphical Techniques
|
|
|
| 6 |
Variability
|
|
|
| 7 |
Measuring Correlation Between Two Variables
|
|
|
| 8 |
Probability
|
|
|
| 9 |
Distributions
|
|
|
| 10 |
Central Limit Theory
|
|
|
| 11 |
Hyphotesis Testing and Confidence Interval
|
|
|
| 12 |
Regression Analysis, Linear Regression
|
|
|
| 13 |
Classification
|
|
|
Contribution of Learning Outcomes to Programme Outcomes
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https://obs.akdeniz.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=2429214&lang=en