Statistics for the labor market 2103-ORP-L-D2STRP
The aim of the lecture is to:
- demonstrate to students the usefulness of statistical research in solving research problems, including those related to the labour market;
- prepare students to independently conduct a basic statistical analysis by familiarising them with:
● methods of processing statistical data;
● key methods of data analysis in the areas of population structure, relationships between variables, and the dynamics of phenomena;
● possibilities for using selected statistical software packages for data analysis and presentation.
In the introductory part, a general overview of statistical methods and basic statistical concepts will be presented. This will be followed by a detailed discussion of the stages and types of statistical research. Subsequent lectures will focus on the presentation of selected statistical methods, such as:
-structural analysis (assessment of the average level, dispersion, skewness, and concentration of a univariate distribution);
- analysis of relationships between variables (correlation analysis of measurable and non-measurable variables);
- dynamic analysis (indices of the dynamics of homogeneous and composite phenomena).
The discussion of each group of methods will be supplemented with examples from real studies conducted in recent years, as well as guidelines on how to prepare data required for a given type of analysis. The final lectures will focus on developing a critical approach to information based on the results of quantitative research. Students will be introduced to critical data analysis through explanations based on real-life examples and equipped with tools to assess the credibility and reliability of data referring to quantitative research results.
The aim of the practical classes is to:
- teach the practical application of knowledge acquired during the lectures;
- motivate students to engage in systematic work;
- develop skills of independent work as well as teamwork.
As part of the classes, students complete a group assignment involving the analysis of statistical data using computer software, the calculation of statistical measures, the selection of appropriate indicators, and the interpretation of results. Students present the results of their own research and critically reflect on them.
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Term 2024L:
The lecture is intended to: - show students the usefulness of statistical research for solving research problems, including those related to the labor market; - prepare students to independently conduct simple statistical analysis by familiarizing them with: ● methods of developing statistical data ● the most important methods of data analysis in the area of community structure, interdependence of features, dynamics of phenomena ● principles of data presentation and analysis The introductory part will present the general characteristics of statistical methods and basic statistical concepts. Then the stages and types of statistical research will be discussed in detail. Subsequent lectures will be devoted to the presentation of selected statistical methods, such as: - structure analysis (assessment of the average level, dispersion, asymmetry and concentration of a one-dimensional distribution), The discussion of each group of methods will be supplemented with examples from real research conducted recently and tips on how to develop the data needed to conduct a given type of analysis. The exercises are intended to: - teach practical use of knowledge acquired during the lecture During the classes, students analyze statistical data, determine statistical measures, select appropriate indicators, interpret results and critically respond to them. |
Term 2025L:
see above (full description in the Basic Course Information) |
Term 2026L:
see above (full description in the Basic Course Information) |
Type of course
Prerequisites (description)
Course coordinators
Mode
Learning outcomes
Upon completion of the course, the student:
- describes tools for acquiring institutional and empirical data related to the labour market (K_W05);
- uses basic statistical concepts and their classifications, as well as key methods of statistical description (K_W05).
The student:
- applies, for practical purposes, knowledge from labour studies to analyse and interpret quantitative data in the field of work and the labour market (K_U01);
- uses acquired statistical knowledge to identify the causes and course of social processes and phenomena occurring in the field of work and the labour market (K_U02);
- operates statistical software for the analysis of statistical data and their graphical presentation, and selects and applies appropriate statistical measures and indicators (K_U03);
- plans and organises their own work, builds a task-oriented team, and cooperates within it to carry out a basic statistical study.
As part of the course, students also acquire social competences. Upon completion of the course, the student:
- is prepared to participate in the preparation of research projects using basic statistical tools;
- critically assesses the reliability and credibility of secondary data based on quantitative research and has tools to verify information derived from research results;
- works effectively in a team using soft skills such as communication, problem-solving, cooperation, planning, and self-management, including time and risk management.
Assessment criteria
A passing grade for the course is required to take the exam. A passing grade for the practical classes is required for passing one colloquium and a group assignment. A maximum of three absences from the practical classes is permitted.
The final exam is written (test).
Lecture + tutorials = 60 hours.
Independent preparation for classes and assessments (group assignment, studying for the exam) = 60 hours.
As part of the course, the use of AI tools is not permitted:
Level 1. NO AI (The verification of learning outcomes is carried out entirely without the assistance of artificial intelligence. Students rely solely on their own knowledge, understanding, and skills. Artificial intelligence may not be used at any stage of assessment.)
Practical placement
not applicable
Bibliography
Maksimowicz-Ajchel A., Wstęp do statystyki. Metody opisu statystycznego, Wydawnictwa Uniwersytetu Warszawskiego, Warszawa 2007.
Arciszewska-Leszczuk, A., Kołek, M. F., Józefacka, N. i Iwankowski, P., Metodologia i statystyka. Przewodnik naukowego turysty. Tom 1, PWN, Warszawa, 2023
Additional literature:
Wieczorkowska G., J. Wierzbiński, Statystyka : analiza badań społecznych, Warszawa: Wydawnictwo Naukowe Scholar, 2010.
Jóźwiak J., J. Podgórski, Statystyka od podstaw, Warszawa: Polskie Wydawnictwo Ekonomiczne, 2012.
Bąk., J., Statystycznie rzecz biorąc. Czyli ile trzeba zjeść czekolady, żeby dostać Nobla? Wydawnictwo W.A.B, 2020.
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Term 2024L:
Maksimowicz-Ajchel A., Wstęp do statystyki. Metody opisu statystycznego, Wydawnictwa Uniwersytetu Warszawskiego, Warszawa 2007. Additional literature: 1. Zeszyt metodologiczny. Statystyka rynku pracy i wynagrodzeń, GUS 2018 |
Term 2025L:
see above (literature in the Basic Course Information) |
Term 2026L:
see above (literature in the Basic Course Information) |
Notes
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Term 2024L:
The condition for admission to the exam is passing the exercises. The final exam is written (test). |
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: