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Regression Analysis: Linear Models

Informacje ogólne

Kod przedmiotu: 2500-EN-S-99 Kod Erasmus / ISCED: 14.4 / (0313) Psychologia
Nazwa przedmiotu: Regression Analysis: Linear Models
Jednostka: Wydział Psychologii
Grupy: specialization courses for 4 and 5 year
Punkty ECTS i inne: 3.00
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 kształcenia: (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.

Zajęcia w cyklu "Semestr zimowy 2017/18" (zakończony)

Okres: 2017-10-01 - 2018-01-26
Wybrany podział planu:


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Typ zajęć: Ćwiczenia, 30 godzin, 13 miejsc więcej informacji
Koordynatorzy: Mikołaj Winiewski
Prowadzący grup: Mikołaj Winiewski
Lista studentów: (nie masz dostępu)
Zaliczenie: Zaliczenie na ocenę
Opisy przedmiotów w USOS i USOSweb są chronione prawem autorskim.
Właścicielem praw autorskich jest Uniwersytet Warszawski.