COURSE INFORMATON
Course Title Code Semester L+P Hour Credits ECTS
Regression Analysis * ISB   321 5 3 3 5

Prerequisites and co-requisites
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 ÖZKALE1. Öğretim Grup:A
Prof.Dr.MAHMUDE REVAN ÖZKALE2. Öğretim Grup:A
 
Assistants
Goals
To construct the necessary theoretical background in undergraduate teaching, to analyze the data that can be faced at the public and private sectors, to gain the knowledge, skills, and practicality for interpreting the results of the analysis.
Content
Parameter estimation and hypothesis testing in simple linear regression model. To detect outliers and influential observations.

Learning Outcomes
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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
X
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
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 Conditional expected value, the concept of regression and model building Source reading
2 The creation of a simple linear regression model, the least squares estimators for the parameters, centered model Source reading
3 Properties of least squares estimators of parameters Source reading
4 Estimation error variance and examination of the properties of the fitted regression model Source reading
5 Maximum likelihood estimation of error variance and regression parameters Source reading
6 Tests of hypotheses about the parameters, test for significance of regression Source reading
7 Preparation and explanation of how to use the ANOVA table, examination of the coefficient of determination Source reading
8 Midterm exam Review the topics discussed in the lecture notes and sources
9 Interval estimation of parameters, the interval estimation of the mean response, prediction of new observations Source reading
10 Regression through the origin, examination of the assumptions of the model (residual analysis), investigation of heteroskedasticity, normal probability graphics Source reading
11 Introduction to outliers and influential observations and examination of their effects on the the least squares estimators Source reading
12 Fitting multiple regression model, matrix notation and estimation of the regression parameters Source reading
13 Examining the distributional properties of least squares estimators of regression parameters, and the error variance Source reading
14 The creation of multiple regression ANOVA table and tests of hypotheses about the parameters of the regression Source reading
15 Determination of the influential observations in multiple regression Source reading
16-17 Final exam Review the topics discussed in the lecture notes and sources

Recommended or Required Reading
Textbook
Additional Resources
Montgomery, D. C., Peck, E. A., Vining, G. G. (2001), Introduction to Linear Regression Analysis, 3rd edition, John Wiely & Sons Inc.