Course aims:

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

Course Entry Requirements:

N/A

Course contents:

Statistical characteristics (variables)
Individual, statistical population and sample
Quantitative characteristics
Measurement scales (metrics)
Frequency distributions
Absolute frequencies, relative frequencies and cumulative frequencies
Weights, percentages, promiles. Graphs attached to frequency distributions
Position indicators of quantitative characteristics
Mean, median and modal value
Dispersion indicators of quantitative characteristics
Amplitude, interquartile deviation, Gini index,
Mean deviation, standard deviation
Using the computer in univariate statistical analysis
Making frequency distributions with the SPSS / PSPP program
Constructing graphs attached to frequency distributions
Calculating position / dispersion indicators with the SPSS / PSPP program
Designing a short questionnaire and using SPSS and PSPP software to build a database (data collected from students of the Sociology department will be used)
Using the database for univariate data analysis
Normal distribution
Properties of the normal distribution
Introductory notions of inferential statistics
Hypothesis testing
Alternative explanations. Analysis with SPSS and PSPP programs.
Correlation and correlation coefficient
Correlation coefficient (Bravais-Pearson).
Rank correlation
Correlation of dummy variables. Using SPSS and PSPP programs.
Linear regression in the case of two variables
General idea of ​​regression.
Equation of the regression line
Quality of estimation
Performing regression analysis with SPSS and PSPP programs
Multiple regression in the case of several independent variables
Regression equation for the relationship between the dependent variable and the independent variables subject to analysis. Analysis with SPSS and PSPP programs.

Teaching methods:

Lecture, Debate, Problematization, Examples and case studies

Learning outcomes:

Manages data in the field of research: Produces and analyzes sociological scientific data from qualitative and quantitative research methods.
Conducts sociological research.
Apply statistical analysis techniques: Uses models (descriptive or inferential statistics) and techniques (data mining or machine learning) for the purpose of statistical analysis, as well as ICT tools to analyze data, discover correlations and forecast trends

Learning outcomes verification and assessment criteria:

Students acquisition of statistical analysis skills of sociological variables and the relationships between them, mainly using common statistical procedures, such as the study of frequency distributions and the correlation

Recommended reading:

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