Regression Analysis: Linear Models
Informacje ogólne
Kod przedmiotu: | 2500-EN-S-99 |
Kod Erasmus / ISCED: |
14.4
|
Nazwa przedmiotu: | Regression Analysis: Linear Models |
Jednostka: | Wydział Psychologii |
Grupy: |
specialization courses for 4 and 5 year |
Punkty ECTS i inne: |
(brak)
|
Język prowadzenia: | angielski |
Rodzaj przedmiotu: | fakultatywne |
Skrócony opis: |
(tylko po angielsku) The course is intended for students that want to learn ordinary least squares (OLS)analysis in order to apply it in their own research and/or to evaluate the work of others. The course will consist of 10h of theoretical lecture and 20h of practical workshop. The focus of LECTURE part will be on reviewing logic of assumptions, possibilities and limitations of OLS regression analysis. The focus of WORKSHOP part will be on practical issues such as selecting the appropriate analysis, preparing data for analysis, interpreting output, and presenting results of a complex nature. The primary goal of the course is to develop an applied and intuitive understanding of the covered statistical material. |
Pełny opis: |
(tylko po angielsku) The course is intended for students that want to learn ordinary least squares (OLS)analysis in order to apply it in their own research and/or to evaluate the work of others. The course will consist of 10h of theoretical lecture and 20h of practical workshop. - The focus of LECTURE part will be on reviewing logic of assumptions, possibilities and limitations of OLS regression analysis. - The focus of WORKSHOP part will be on practical issues such as selecting the appropriate analysis, preparing data for analysis, interpreting output, and presenting results of a complex nature. The primary goal of the course is to develop an applied and intuitive understanding of the covered statistical material. Covered material will deal mostly with Multiple Regression analysis including: Model specification and interpretation Diagnostics (tests and plots) Analysis of residuals and outliers Multicollinearity Autocorrelation Hierarchical models Dummy (dichotomous) independent variables Dummy coding of nominal variables Inducing linearity by nonlinear transformations of independent variables Multiplicative Interaction terms Mediation analysis Specific topics and amount of covered material will depend in part on the interests of the students and class progress. |
Literatura: |
(tylko po angielsku) Handbook: Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2013). Applied multiple regression/correlation analysis for the behavioral sciences. Routledge. |
Efekty uczenia się: |
(tylko po angielsku) Students Will learn the basics assumptions and logic behind OLS regression analysis Will develop skills with a range of practical procedures in order to diagnose and prepare data, build model and eventually run OLS regression analysis. get acquainted with the statistical computing system SPSS/PASW and with its use for manipulation and analysis of statistical data. |
Metody i kryteria oceniania: |
(tylko po angielsku) Student performance will be assessed base on preparation (reading assigned literature and home assignments), class activities (class performance, solving tasks assigned in class, in-class activity) and final test. homework (20%) literature quizzes (15%) class activities (15%) final test (50%) Students may have maximum 2 absences. |
Właścicielem praw autorskich jest Uniwersytet Warszawski, Wydział Chemii.