Introduction to quantitative and qualitative data analysis programs

Type of course:	Elective (1 of 2)
Language of instruction:	Romanian
Erasmus Language of instruction:	English
Name of lecturer:	Vlad Zeno Millea
Seminar tutor:	Vlad Zeno Millea
Form of education	Full-time

Form of instruction:	Class / Seminary
Number of teaching hours per semester:	56
Number of teaching hours per week:	4
Semester:	Autumn
Form of receiving a credit for a course:	Grade
Number of ECTS credits allocated	4

Course aims:

Training students' abilities to build and manage correctly databases used by the usual statistical analysis software (Excel, SPSS, PSPP)
Correct use of basic techniques for multivariate analysis of qualitative data, especially association tables, with SPSS and PSPP programs
Acquisition of skills for sociological interpretation of statistical outputs ("the reading of" tables, graphs and indicators calculated using the SPSS or PSPP program)

Course Entry Requirements:

N/A

Course contents:

Individual, statistical population and sample Qualitative and quantitative characteristics Frequency distributions Weights, percentages, per thousand Position indicators of quantitative characteristics Mean, median and modal value Dispersion indicators of quantitative characteristics Amplitude, interquartile range deviation, Gini index, Mean deviation, standard deviation Using the computer in univariate statistical analysis Designing a short questionnaire and using SPSS and PSPP software to build a database (data from Sociology students will be used) Bivariate analysis of qualitative characteristics dichotomous characteristics Applications of the statistical independence table in the definition and calculation of association coefficients Association of nominal qualitative characteristics Association of ordinal qualitative characteristics Coefficient τa (of Kendall) and Coefficients τb and τc (of Kendall) Analysis, with SPSS and PSPP, of the association tables with dichotomous variables

Teaching methods:

Lectures, conversations, demonstrations

Learning outcomes:

Acquire, by the students, the skills of statistical analysis of sociological variables and of their relationships using mainly common statistical procedures, such as the study of frequency distributions and the association of qualitative characteristics (using the support of software dedicated to statistical analysis of data such as SPSS and PSPP

Learning outcomes verification and assessment criteria:

Elaboration of a paper for 2 hours that reflects 60% of the final grade and an analysis of a database that reflects 40% of the final grade