API-303 / GENERAL LİNEAR MODELS
| KOD |
: |
APİ-303 |
| BAŞLIK |
: |
GENEL DOĞRUSAL MODELLER |
| İNGİLİZCE BAŞLIK |
: |
GENERAL LİNEAR MODELS |
| TÜR (Zorunlu / Seçmeli) |
: |
SEÇMELİ |
| AKTS DEĞERİ |
: |
7,5 |
| KADEME (Yüksek Lisans / Doktora) |
: |
YÜKSEK LİSANS |
| DÖNEMİ |
: |
GÜZ DÖNEMİ |
| DERSİN VERİLDİĞİ ABD ve PROGRAMI |
: |
ADLİ PSİKOLOJİ |
| DERSİ VEREN ÖĞRETİM ELEMANI |
: |
DR. ÖĞR. ÜYESİ DERYA AZIK ÖZKAN |
DERSİN TANIMI
This course introduces students to techniques of data analysis and statistical inference based on the general linear model. The bulk of the course is devoted to linear regression analysis of continuous outcomes. In addition, techniques for logistic regression (for dichotomous and categorical outcomes) are covered.
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DERSİN AMACI
By the end of the course the student should demonstrate the ability to:
• identify continuous and discrete (or categorical) variables as either dependent or independent, and choose appropriate statistical procedures for their analysis;
• describe relationships between predictor variables and a continuous outcome variable;
• calculate point estimates and confidence intervals and conduct hypothesis testing for regression slopes;
• delineate assumptions of linear statistical models and examine data to evaluate their conformity to those assumptions;
• formulate and interpret multiple regression models appropriate for various research problems and interpret computer output relevant to those models;
• recognize similarities and differences between regression and analysis-of-variance models;
• describe relationships between predictor variables and a dichotomous outcome variable via binary logistic regression;
• calculate and interpret regression parameters for binary logistic regression models;
• conduct analyses to diagnose problems with multicollinearity, influential points, etc., for binary logistic regression;
• write coherent summaries and interpretations of data analyzed by the above procedures.
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DEĞERLENDİRME YÖNTEMİ (Sınav, Ödev, Sunum vb.)
Midterm exam, final exam, assignments.
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| HAFTA |
: |
KONU BAŞLIKLARI |
| 1. HAFTA |
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SYLLABUS & INTRO |
| 2. HAFTA |
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SIMPLE REGRESSION |
| 3. HAFTA |
: |
SIMPLE REGRESSION |
| 4. HAFTA |
: |
MULTIPLE REGRESSION |
| 5. HAFTA |
: |
MULTIPLE REGRESSION |
| 6. HAFTA |
: |
MULTIPLE REGRESSION |
| 7. HAFTA |
: |
DUMMY, INTERACTION, AND RELATION TO ANOVA |
| 8. HAFTA |
: |
MIDTERM EXAM |
| 9. HAFTA |
: |
ANCOVA MODEL |
| 10. HAFTA |
: |
ATI MODEL, NONLİNEAR REGRESSİON |
| 11. HAFTA |
: |
LOGİSTİC REGRESSİON (BİNARY) |
| 12. HAFTA |
: |
LOGİSTİC REGRESSİON (BİNARY) |
| 13. HAFTA |
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LOGİSTİC REGRESSİON (ORDERED CATEGORİCAL) |
| 14. HAFTA |
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REVİEW FOR FİNAL |
Ders İçin Önerilen Kaynakça
Cohen, J., Cohen, P., West, S. & Aiken, L. S. (2010). Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences (3rd ed).