Ders Planı

Lesson Information

Course Credit	3.0
Course ECTS Credit	4.0
Teaching Language of Instruction	Türkçe
Level of Course	Bachelor's Degree, TYYÇ: Level 6, EQF-LLL: Level 6, QF-EHEA: First Cycle
Type of Course	Compulsory
Mode of Delivery	Face-to-face
Does the course require compulsory or optional work experience?	Z
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Purpose and Content

The aim of the course	This course teaches regression Analysis,in univariate (linear) and multivariate regression analysis to practice on. Analysis is related to each other to affect the status of the various variables. Students will apply for the regression analysis of the various econometric models.
Course Content	Students will acquire simple Linear Regression and Correlation; Multiple Linear Regression; variable selection procedures, Residual Analysis; Polynomial Regression Models; Indicator Variables; Model Building; Multicollinearity; use of transformations, Non-linear regression, the use of indicator variables, and logistic regression, Use of SAS.

Learning Outcomes

Has theoretical knowledge in the field of statistics.
Has the ability to use the theoretical resources required for statistics
Has the ability to use the theoretical resources required for statistics
To be able to use the necessary theoretical content resources for statistics
Defines the studies related to statistics independently and with the partners
Describe the current problems with statistical methods
Defines the ability of abstract and analytical thinking
Comprehend the knowledge of computer software and programming technique to be able to apply the science of statistics effectively.
Analyze the theoretical knowledge in probability and statistics
Evaluate different databases as required
Evaluates the outputs of applied questionnaires
Applies the concepts and thoughts in the field with scientific methods
Arrange the data related to the field
Solve the identified statistical problems
Prepares surveys
Develops solutions based on identified statistical problems, evidence and research
Contributes to the professional development of the employees under their management
Define new topics related to statistics
Give lectures and seminars about statistics and probability
Determines the needs for learning
Develops original attitudes towards lifelong learning by guiding learning processes related to learning
He/She organizes projects and activities for the social environment in which he/she lives with an awareness of social responsibility
Students will be able to communicate their solutions to problems related to statistics in written and oral forms
Supports suggestions for solutions and thoughts with quantative and quantative data
Follow developments in the field by using a foreign language
Uses computer software and information-communication-network technologies at the level required by the science of statistics
Students will have social, scientific and ethical values in the publication of the data related to the fields of science
Quality management and process, environmental protection, occupational health and safety issues has sufficient awareness
Gain social, scientific and ethical values in the stages of collecting, interpreting and announcing the data related to the fields of science
Has knowledge about the legal consequences of statistical applications

Weekly Course Subjects

1	Introduction to the regression model
2	Simple regression model and applications
3	Multiple regression and applications
4	Hypothesis Testing of estimators and estimated values.
5	Complex models
6	Nonlinear regression
7	Selection the best regression model
8	Simultaneously equations
9	Midterm and solving problems
10	Multicollinearity and ridge regression
11	Otocorrelation and applications
12	Estimation methods in regression
13	Orthogonal polinoms in regression.
14	Transformations in regression model.

Resources

1.Prof.Dr. Besim Akin, Çözümlü Örneklerle Uygulamalı istatistik, İstanbul Ofset Basım Yayım, 2010, İstanbul.

2.Prof.Dr.Meriç Öztürkcan, Regresyon analizi, Maltepe Üniversitesi Yayınları, No:40, İstanbul,2009

3.Akdeniz, F., Olasılık ve İstatistik, Ankara Üni., Fen Fak., Yayını, 1984

4.Özkan Ünver, Hamza Gamgam, B.Altun Kaynak, Temel İstatistik Yöntemler, seçkin yayınevi(SPSS Uygulamalı),Ankara, 2011
5. Draper, N. R. and Smith, H., Applied Regression Analysis, John Wiley and Sons, N.V., 1966

6. Ezekiel Mordecai, FOX Karl A., Methods of Correlation and Regression Analysis, John Wiley and Sons, N.V, 1961

7. Dixon Wilfrid J., Massey Frank J., Introduction to statistical, Mc Graw - Hill Kogakusha Ltd., 1969

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CLASS 2

CLASS 3

CLASS 4

Lesson Information

Purpose and Content

Learning Outcomes

Weekly Course Subjects

Resources

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