﻿ IST311

IST311

Course Title Course Code Program Level
REGRESSION ANALYSIS IST311 Statistics B.A. / B.Sc.

Course Term
(Course Semester)
Teaching and Learning Methods
Credits
Theory Practice Lab Projects/Field Work Seminars/Workshops Other Total Credits ECTS Credits
05
(Fall)
42 40 58 140 3 6

Teaching Staff
Language of Instruction Türkçe (Turkish)
Type Of Course Compulsory
Prerequisites Linear Algebra & Statistikal Methods 1, 2
Recommended Optional Programme Component
Course Objectives To teach Bivariate regression: Fitting Data a straight line, The Method of Least Squares, Bivariate regression: Assumption and inference, Multiple regression, Multicollinearity problem and Model selection.
Course Content To teach Bivariate regression: Fitting Data a straight line, The Method of Least Squares, Bivariate regression: Assumption and inference, Multiple regression, Multicollinearity problem and Model selection.
Learning Outcomes (LO) To teach Bivariate regression: Fitting Data a straight line, The Method of Least Squares, Bivariate regression: Assumption and inference, Multiple regression, Multicollinearity problem and Model selection.
Mode of Delivery Face to face
Course Outline
Week Topics
1. Week Basic Conpets & Scatter Plot
2. Week Simple Linear Regression Model & The Least Squares Method
3. Week Model Assumptions, Sum of Squares, Determination Coefficient
4. Week Confidence Intervals & Significance Tests
5. Week Confidence Intervals & Significance Tests
6. Week Parameter Estimations & Computing Variations by using Matrix Operations
7. Week The Multiple Regression Model & Parameter Estimation
8. Week The Multiple Correlation Coefficient, Statistical Inferences of The Multiple Regression Model
9. Week Statistical Inferences of The Multiple Regression Model
10. Week Part and Partial Correlation, The Usage of The Dummy Coefficient
11. Week The Weighted Least Squares Method, The Examination of Excess Terms
12. Week The Correlation Matrix, Multiple Connecitons
13. Week Coefficient Selection Methods
14. Week Coefficient Selection Methods & Autocorrelation
Assessment
 Percentage(%) Mid-term (%) 40 Quizes (%) Homeworks/Term papers (%) Practice (%) Labs (%) Projects/Field Work (%) Seminars/Workshops (%) Final (%) 60 Other (%) Total(%) 100
Course Book (s) and/or References 1. Draper, N. R. and Smith, H., 1996, Applied Regression Analysis,  New York. 2. Ünver, Ö. ve Gamgam, H. 2008 Uygulamalı TEMEL İSTATİSTİK YÖNTEMLER, Seçkin Yayınevi, Ankara
Work Placement(s)
The Relationship between Program Qualifications (PQ) and Course Learning Outcomes (LO)