GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
STATISTICAL ANALYSIS/2080050
Course Title: STATISTICAL ANALYSIS
Credits 3 ECTS 7.5
Semester 2 Compulsory/Elective Elective
COURSE INFO
 -- LANGUAGE OF INSTRUCTION
  Turkish
 -- NAME OF LECTURER(S)
  Ass.Prof.Yeliz Yalcin, Assoc. Prof. Furkan EMIRMAHMUTOGLU
 -- WEB SITE(S) OF LECTURER(S)
  http://websitem.gazi.edu.tr/site/yyeliz, http://websitem.gazi.edu.tr/site/furkan
 -- EMAIL(S) OF LECTURER(S)
  yyeliz@gazi.edu.tr, emirfurkan@gmail.com
 -- LEARNING OUTCOMES OF THE COURSE UNIT
Students will have known some important distributions and their properties
Students will have learn the small and large sample properties of estimator
Students will have learned the asyptotic theory
Students will have learned estimation theory and hypothesis testing
 -- MODE OF DELIVERY
  The mode of delivery of this course is Face to face
 -- PREREQUISITES AND CO-REQUISITES
   There is no prerequisite or co-requisite for this course.
 -- RECOMMENDED OPTIONAL PROGRAMME COMPONENTS
  There is no recommended optional programme component for this course.
 --COURSE CONTENT
1. Week  Introduction
2. Week  Some Important Distributions and their properties Normal Distribution, Chi-Square, t, F
3. Week  Some Important Distributions and their properties Logistic, Beta, Gamma, Wiashart
4. Week  Estimation and Statistical Inference
5. Week  Estimation and Statistical Inference
6. Week  Small Sample properties of Estimator unbiasedness, efficient, Mean square error, Cramér-Rao lower bound , sufficiency,consistency
7. Week  Small Sample properties of Estimator unbiasedness, efficient, Mean square error, Cramér-Rao lower bound , sufficiency,consistency
8. Week  I. midterm
9. Week  Asyptotic Properties
10. Week  Large Sample properties of Estimator Asymptotic unbiasedness, Asymptotic consistency, Asymptotic Efficiency
11. Week  Large Sample properties of Estimator Asymptotic unbiasedness, Asymptotic consistency, Asymptotic Efficiency
12. Week  Estimation Methods (ML, OLS, MM, Bayes)
13. Week  Estimation Methods (ML, OLS, MM, Bayes)
14. Week  Hyphotesis Testing (LR, Wald, LM )
15. Week  Hyphotesis Testing (I.type error, II. type Error, Power of test)
16. Week  Final
 -- RECOMMENDED OR REQUIRED READING
  Yılmaz Akdi, Matematiksel İstatistiğe Giriş, Gazi Kitapevi, 2010 William H. Greene, Econometric Analysis, Prentice Hall, 2011
 -- PLANNED LEARNING ACTIVITIES AND TEACHING METHODS
  Lecture, Question & Answer
 -- WORK PLACEMENT(S)
  Not Applicable
 -- ASSESSMENT METHODS AND CRITERIA
 
Quantity
Percentage
 Mid-terms
1
50
 Assignment
0
0
 Exercises
0
0
 Projects
0
0
 Practice
0
0
 Quiz
0
0
 Contribution of In-term Studies to Overall Grade  
50
 Contribution of Final Examination to Overall Grade  
50
 -- WORKLOAD
 Efficiency  Total Week Count  Weekly Duration (in hour)  Total Workload in Semester
 Theoretical Study Hours of Course Per Week
14
3
42
 Practising Hours of Course Per Week
13
2
26
 Reading
13
3
39
 Searching in Internet and Library
13
3
39
 Designing and Applying Materials
14
2
28
 Preparing Reports
0
 Preparing Presentation
0
 Presentation
0
 Mid-Term and Studying for Mid-Term
2
3
6
 Final and Studying for Final
2
4
8
 Other
0
 TOTAL WORKLOAD: 
188
 TOTAL WORKLOAD / 25: 
7.52
 ECTS: 
7.5
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
 PROGRAM LEARNING OUTCOMES
1
2
3
4
5
1Having the professional expertise and skills on theoretical and practical aspect of econometrics.X
2Having appropriate behavior of econometricsin the field of social, scientific, cultural and ethical values, applicability of gained knowledge and skills in accordance with the principle of responsibility to social and working life.X
3Having skills about selecting, using and evaluating of appropriate econometrics and statistical programming methods, based on theoretical and practical knowledge acquired in the field related to the current problems faced by.X
4Having skills to work with the team for reach fruitful results in interdisciplinary and interdisciplinary studies.X
5Having knowledge of research methods in the field of institutions and organizations planning projects, managing in order to conduct independent research.X
6Using some of the advanced level econometrics and statistical software programs.X
7Having skills about information system related to the fields in working life.
8Having qualities for analytical thinking, prospecting and bring scientific solutions to problems as a researcher.
9Having skills to comprehension, application and evaluation about terms and basic theory of operational research.
10Having the professional expertise and skills on theoretical and practical aspects of operational research.