COURSE INFORMATON
Course Title Code Semester L+P Hour Credits ECTS
Statistical Methods * TMZ   203 3 2 2 3

Prerequisites and co-requisites Yok
Recommended Optional Programme Components None

Language of Instruction Turkish
Course Level First Cycle Programmes (Bachelor's Degree)
Course Type
Course Coordinator Prof. Dr. Güzin YÜKSEL
Instructors
Prof. Dr.GÜZİN YÜKSEL1. Öğretim Grup:A
 
Assistants
Goals
The aim of this course is to teach basic concepts, principles, techniques of science of statistics and the terminology that is required for them; to earn the competency/ability to appropriately use and interpret statistical concepts, principles and techniques.
Content
Basic Concepts,Types Of Data, Data Sources, Data Collection Techniques, Sampling Techniques, Frequency Distributions, Measure of Central Tendencies, Measure of Variability, Measure of Skewness and Measure of Kurtosis, Probability and Special Probability Distributions, Normal Distribution, Confidence intervals, Hypothesis testing, Regression

Learning Outcomes
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Course's Contribution To Program
NoProgram Learning OutcomesContribution
12345
1
Has sufficient background in the fields of Mathematics, Science and Textile Engineering
2
Uses the knowledge obtained from the basic sciences and engineering in the field of textile engineering
3
Does process analysis, Identifies problems, interprets and evaluates data in the field of textile engineering
4
Selects and uses modern techniques and tools for engineering applications
5
Has the skills of designing experiments, data collection, cognitive analysis and interpretation of the results
6
Works effectively both individually and as a team member and takes responsibility
7
Searches literature, has access to information, uses databases and other sources of information
8
Recognizes the need of lifelong learning; follows developments in science and technology and renews self continuosly
9
Has effective oral and written communication skills.
10
Follows developments in the field in a foreign language, has good communication skills with colleagues.
11
Uses information and communication technologies and softwares at a required level
12
Defines learning requirements in scientific, social, cultural and artistic areas and improves himself/herself accordingly.
13
Has the professional and ethical responsibility.
14
Has the necessary awareness on the fields of occupational health and safety, legal side of engineering applications and environmental health.
15
Has required competence in project management, entrepreneurship and innovation.

Course Content
WeekTopicsStudy Materials _ocw_rs_drs_yontem
1 Basic Concepts Reading the source
2 Types Of Data, Data Sources Reading the source, problem solving
3 Data Collection Techniques Reading the source, problem solving
4 Sampling Techniques Reading the source, problem solving
5 Frequency Distributions Reading the source, problem solving
6 Measure of Central Tendencies Reading the source, problem solving
7 Measure of Variability, Measure of Skewness and Measure of Kurtosis Reading the source, problem solving
8 Midterm Review the topics discussed in the lecture notes and sources
9 Probability and Special Probability Distributions Reading the source, problem solving
10 Special Probability Distributions Reading the source, problem solving
11 Normal Distribution Reading the source, problem solving
12 Confidence intervals Reading the source, problem solving
13 Hypothesis testing Reading the source, problem solving
14 Regression Reading the source, problem solving
15 Regression Reading the source, problem solving
16-17 Final Exam Review the topics discussed in the lecture notes and sources

Recommended or Required Reading
Textbook
Additional Resources
Ders Notu ve Kitaplar