•
•           Information on Degree Programmes

COURSE INFORMATON
Course Title Code Semester L+P Hour Credits ECTS
Biostatistics * ISB   462 8 3 3 5

 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. Mahmude Revan ÖZKALE
Instructors
 Prof. Dr. MAHMUDE REVAN ÖZKALE 1. Öğretim Grup:A Prof. Dr. MAHMUDE REVAN ÖZKALE 2. Öğretim Grup:A

Assistants
Goals
Statistical modeling and interpeting the econometric data
Content
Multiple linear regression model, heteroscedasticity, multicollineairt problem, dummy variable models, distributed lag models

Learning Outcomes
-

Course's Contribution To Program
NoProgram Learning OutcomesContribution
12345
1
Explain the essence fundamentals and concepts in the field of Probability, Statistics and Mathematics
X
2
Emphasize the importance of Statistics in life
X
3
Define basic principles and concepts in the field of Law and Economics
4
Produce numeric and statistical solutions in order to overcome the problems
X
5
Use proper methods and techniques to gather and/or to arrange the data
X
6
Utilize computer systems and softwares
7
Construct the model, solve and interpret the results by using mathematical and statistical tehniques for the problems that include random events
X
8
Apply the statistical analyze methods
X
9
Make statistical inference(estimation, hypothesis tests etc.)
X
10
Generate solutions for the problems in other disciplines by using statistical techniques
X
11
Discover the visual, database and web programming techniques and posses the ability of writing programme
12
Construct a model and analyze it by using statistical packages
X
13
Distinguish the difference between the statistical methods
X
14
Be aware of the interaction between the disciplines related to statistics
X
15
Make oral and visual presentation for the results of statistical methods
X
16
Have capability on effective and productive work in a group and individually
X
17
Professional development in accordance with their interests and abilities, as well as the scientific, cultural, artistic and social fields, constantly improve themselves by identifying training needs
18
Develop scientific and ethical values in the fields of statistics-and scientific data collection
X

Course Content
WeekTopicsStudy Materials _ocw_rs_drs_yontem
1 Introduction to Econometrics, examination of the deviations from the assumptions of multiple regression analysis Source reading
2 Investigate the properties of the estimators, hypothesis testing in multiple lnear regession model Source reading
3 Confidence interval in multiple lnear regession model, matrix approximaitons to multiple linear regression model Source reading
4 Multicollinearity problem (identification and correction of multicollinearity) Source reading
5 Some biased estimators in the problem of multicollinearity Source reading
6 Determination of heteroscedasticity, systematic and non-systematic tests (Goldfeld Quant, Park ve Glejser testsi) Source reading
7 Breusch Pagan Godfrey test from systematic test and correction of heteroscedasticity Source reading
8 Midterm exam Review the topics discussed in the lecture notes and sources
9 Dummy variable models Source reading
10 Dummy variable models Source reading
11 Qualitative dependent variable regression models (DOM and Logit models) Source reading
12 Qualitative dependent variable regression models (Logit and Probit models) Source reading
13 Distributed Lag models (estimation by least squares, Koyck model and Almon polynomial lag model) Source reading
14 Distributed Lag models (estimation by Nerlove s partial adjustment model and Cagan s adptive expectation model) Source reading
15 Autoregressive models Source reading
16-17 Final exam Review the topics discussed in the lecture notes and sources

Recommended or Required Reading
Textbook