1. SylabUZ
2. Wydział Nauk Społecznych
3. semestr zimowy 2018/2019
4. Sociology - drugiego stopnia z tyt. magistra
5. Advanced Computer Analysis of Data

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Advanced Computer Analysis of Data - opis przedmiotu

Cel przedmiotu

Preparing students to apply advanced procedures for analysis of the survey data and their practical use: calculation, analysis and interpretation of the results of empirical research. Acquiring skills of using an IBM SPSS Statistics.

Wymagania wstępne

Zapisz zmiany

-

Zakres tematyczny

1. Managing data sets.
2. Operations on data. Creating new variables.
3. Creating indexes. Analysis of reliability.
4. Multi-variable analysis-analysis of variance, correlation, factor analysis, linear regression, cluster analysis.
5. Problems for the interpretation of survey data.
6. Working with own research project.

Metody kształcenia

Problem-solving laboratory method, the method of practical sessions

Efekty uczenia się i metody weryfikacji osiągania efektów uczenia się

Opis efektu	Symbole efektów	Metody weryfikacji	Forma zajęć

Warunki zaliczenia

 

FORM OF ASSESSMENT OF CLASSES	REMARKS
Grade	Yes
Written mid-term exam.	Tasks implemented using IBM SPSS Statistics The minimum threshold requirements is to give at least 50% correct answers to the questions. At least two mid-term exam are expected.
Range of material covering the mid-term exam.	In accordance with the first class Syllabus: connecting sets, data analysis in subgroups, the choice of observation to analysis), data transformation procedures, covariance analysis (measure of the relation strength and correlation), data reduction using factor analysis and cluster analysis,explanatory models-regression analysis, creating indexes (using the researcher’s algorithm) and the analysis of their reliability; analysis of variance (ANOVA).
Implementation of the tasks provided for the program.	Connecting sets, data analysis in subgroups, the choice of observation to analysis), data transformation procedures, covariance analysis (measure of the relation strength and correlation), data reduction using factor analysis and cluster analysis, explanatory models-regression analysis, creating indexes (using the researcher’s algorithm) and the analysis of their reliability; analysis of variance (ANOVA). Student must do all the task and save the results in his/sher own folder.
Criteria for final grade assessment  for classes.	Classes grade will be the arithmetic mean of all mid-term exams.

The final grade is the grade of the classes

Literatura podstawowa

http://www.academia.dk/BiologiskAntropologi/Epidemiologi/PDF/SPSS_Statistical_Analyses_using_SPSS.pdf

http://www.statisticssolutions.com/factor-analysis-2/

 

Literatura uzupełniająca

Exercises and own materials of the lecturer.

Uwagi

Students can receive, during the whole learning cycle, a licensed within ARIADNA program version of the IBM SPSS Statistics (new version each year) to be used in the implementation of their own projects.

Zmodyfikowane przez dr Dorota Bazuń (ostatnia modyfikacja: 02-05-2018 13:25)