GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
STATISTICAL DATA ANALYSIS/ENM356
Course Title: STATISTICAL DATA ANALYSIS
Credits 3 ECTS 4
Course Semester 6 Type of The Course Elective
COURSE INFORMATION
 -- (CATALOG CONTENT)
 -- (TEXTBOOK)
 -- (SUPPLEMENTARY TEXTBOOK)
 -- (PREREQUISITES AND CO-REQUISITES)
 -- LANGUAGE OF INSTRUCTION
  Turkish
 -- COURSE OBJECTIVES
 -- COURSE LEARNING OUTCOMES
An ability to apply knowledge of mathematics, science, and engineering
An ability to design and conduct experiments, as well as to analyze and interpret data
An ability to design a system, component, or process to meet desired needs
An ability to identify, formulate, and solve engineering problems
An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice
 -- MODE OF DELIVERY
  The mode of delivery of this course is Face to face
 --WEEKLY SCHEDULE
1. Week  Basic concepts, data collection, types of data and sampling
2. Week  Graphical and Numerical methods for describing qualitatif and quantitatif data
3. Week  Graphical methods and ChiSquare, Kolmogorv Smirnov Tests.
4. Week  Design and analysis of single factor experiments, fixed effects models.
5. Week  Tests on individual treatments (Least Significant Difference Method, Duncan’s method)
6. Week  Random effects models.
7. Week  Factorial experiments, two factor factorial experiments, fixed effects model, random effects model
8. Week  Factorial experiments, two factor factorial experiments, fixed effects model, random effects model
9. Week  Simple linear regression, hypothesis testing in simple linear regression
10. Week  Interval estimation in simple linear regression, measuring the adequacy of the regression model, correlation.
11. Week  Multiple regression models, estimation of parameters, confidence intervals and hypothesis testing in multiple linear regression
12. Week  Measures of model adequacy, polynomial regression.
13. Week  Non-parametric tests: Sign test, Wilcoxon Signed Rank test
14. Week  Non-parametric tests: Mann-Whitney U test, Median test
15. Week  
16. Week  
 -- TEACHING and LEARNING METHODS
 -- ASSESSMENT CRITERIA
 
Quantity
Total Weighting (%)
 Midterm Exams
1
40
 Assignment
5
10
 Application
0
0
 Projects
0
0
 Practice
0
0
 Quiz
1
10
 Percent of In-term Studies  
60
 Percentage of Final Exam to Total Score  
40
 -- WORKLOAD
 Activity  Total Number of Weeks  Duration (weekly hour)  Total Period Work Load
 Weekly Theoretical Course Hours
14
3
42
 Weekly Tutorial Hours
0
 Reading Tasks
0
 Searching in Internet and Library
2
4
8
 Material Design and Implementation
5
3
15
 Report Preparing
0
 Preparing a Presentation
0
 Presentation
0
 Midterm Exam and Preperation for Midterm Exam
1
15
15
 Final Exam and Preperation for Final Exam
1
20
20
 Other (should be emphasized)
0
 TOTAL WORKLOAD: 
100
 TOTAL WORKLOAD / 25: 
4
 Course Credit (ECTS): 
4
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
 PROGRAM LEARNING OUTCOMES
1
2
3
4
5
1Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledge in these areas in complex engineering problems.X
2Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purposeX
3Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose...X
4Ability to devise, select, and use modern techniques and tools needed for analyzing and solving complex problems encountered in engineering practice; ability to employ information technologies effectively
5Ability to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or discipline specific research questionsX
6Ability to work efficiently in intradisciplinary and multi-disciplinary teams; ability to work individually
7Ability to communicate effectively in Turkish, both orally and in writing knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions
8Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself
9Consciousness to behave according to ethical principles and professional and ethical responsibility; knowledge on standards used in engineering practice .
10Knowledge about business life practices such as project management, risk management, and change management; awareness in entrepreneurship, innovation; knowledge about sustainable development
11Knowledge about the global and social effects of engineering practices on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; awareness of the legal consequences of engineering solutions .
 -- NAME OF LECTURER(S)
   (Prof. Dr. Fulya Altıparmak , Prof. Dr. Ömer Faruk Baykoç)
 -- WEB SITE(S) OF LECTURER(S)
   (https://websitem.gazi.edu.tr/site/fulyaal , https://websitem.gazi.edu.tr/site/baykoc)
 -- EMAIL(S) OF LECTURER(S)
   (fulyaal@gazi.edu.tr , baykoc@gazi.edu.tr)