Introduction to Data Analysis (Computer laboratories) 480-ERS-1IDA

This course provides an introductory exploration of quantitative data analysis techniques applied to sociological research. Students will develop key skills necessary for processing, analyzing, and interpreting data by working with real-world and simulated datasets in a computer laboratory environment.

The course is designed to build competencies in handling basic statistical operations using popular analytical software such as SPSS, R, or Excel. Emphasis will be placed on practical understanding—students will not only compute statistical measures but also interpret their meaning within the context of social science problems. Participants will learn how to organize data, describe patterns, investigate relationships between variables, and critically assess research findings.

Through interactive sessions, students will practice preparing simple tables, charts, and reports suitable for academic and professional contexts. The knowledge and skills acquired will form the basis for more advanced quantitative methods courses, as well as for practical application in research projects, bachelor's theses, or sociological reports.

Introduction to Quantitative Data in Sociology
Understanding types of data and variables; examples from social surveys.

Building a Dataset
Data entry, coding, and preparing a database for analysis.

Descriptive Statistics
Calculating means, medians, modes, standard deviations, and interpreting their sociological significance.

Data Visualization
Creating and interpreting frequency tables, bar charts, histograms, and pie charts.

Exploring Relationships Between Variables
Introduction to cross-tabulation, correlation coefficients, and their meaning in social research.

Introduction to Inferential Statistics
Basic concepts of sampling and the chi-square test for independence.

Practical Software Workshops
Step-by-step use of SPSS, R, and Excel for dataset management and basic analyses.

Final Project Preparation
Conducting a small-scale analysis using provided data and presenting findings in a structured report.

Rodzaj przedmiotu

obowiązkowe

Założenia (opisowo)

This course is designed to introduce sociology students to the basics of quantitative data analysis using computer-based tools. The focus is on the practical application of descriptive statistics and basic data analysis methods relevant to social research. Students will develop skills in using software such as SPSS, R, or Excel to input, manage, and interpret datasets. The course aims to prepare students for independent work with simple social data analyses, essential for further academic projects and research work.

Koordynatorzy przedmiotu

Maciej Białous

Efekty kształcenia

Knowledge (S2_W)
S2_W05: Has basic knowledge about methods of quantitative data analysis in sociological research.

S2_W06: Knows and understands fundamental concepts of descriptive statistics and their application in social data analysis.

Skills (S2_U)
S2_U07: Can independently conduct basic quantitative data analyses using appropriate software (e.g., SPSS, R, Excel).

S2_U08: Is able to interpret the results of statistical analyses and formulate conclusions concerning social phenomena.

Social Competences (S2_K)
S2_K03: Is aware of the importance of reliability and ethics in conducting data analyses and presenting research results.

S2_K04: Can collaborate effectively in a team when carrying out analytical projects, sharing knowledge and skills.

Kryteria oceniania

Continuous assessment based on the results achieved during each laboratory session. Students develop their final project gradually throughout the semester, and their progress and active participation are evaluated systematically.

Literatura

Required Reading:
Field, A. (2018). Discovering Statistics Using IBM SPSS Statistics (5th Edition). SAGE Publications.
(Comprehensive and accessible textbook covering practical use of SPSS for social sciences.)

Bryman, A. (2016). Social Research Methods (5th Edition). Oxford University Press.
(Chapters on quantitative research, data collection, and basic data analysis.)

Healey, J. F. (2015). Statistics: A Tool for Social Research (10th Edition). Cengage Learning.
(Clear explanations of statistical concepts and procedures in a social science context.)

Recommended Reading:
Pallant, J. (2020). SPSS Survival Manual (7th Edition). McGraw-Hill Education.
(Step-by-step guide to statistical analysis using SPSS.)

R Core Team. (2024). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing.
(Open-source manual and documentation for R users.)

Babbie, E. (2020). The Practice of Social Research (15th Edition). Cengage Learning.
(Classic text on research methods, including basics of survey design and data interpretation.)

Agresti, A., & Finlay, B. (2009). Statistical Methods for the Social Sciences (4th Edition). Pearson.
(In-depth treatment of statistical analysis for advanced students.)

Więcej informacji

Dodatkowe informacje (np. o kalendarzu rejestracji, prowadzących zajęcia, lokalizacji i terminach zajęć) mogą być dostępne w serwisie USOSweb:

Strona przedmiotu 480-ERS-1IDA w USOSweb