Social statistics 2103-L-D2STSP
The lecture aims at:
- showing students that statistical research is a useful tool to deal with research problems,
- preparing the students to conduct statistical research on their own by making them familiar with:
● the methods of collecting and organizing statistical data,
● the most important methods of data analysis within the scope of
population structure, association of variables and phenomenon
dynamics,
● the ways of using chosen statistical paskage for statistical data analysis and presentation
The introductory part will deal with general characteristics of statistical methods, basic statistical concepts and their classifications. Next, we will discuss in detail the stages and types of statistical research. The subsequent lectures will be devoted to the presentation of selected statistical methods, such as:
- analysis of population structure (measures of central tendency, variation, shape and concentration)
- simple correlation and regression (measuring the strength of the association of quantitative and qualitative variables, simple linear regression)
- time-series analysis (individual and aggregate index of dynamics)
The discussion of each group of methods will be preceded by an explanation of how to organize data for the purpose of a given analysis and supplemented by empirical examples and the presentation of the possibilities of using statistical package/program for statistical analysis.
The classes aim at:
- teaching students how to apply the theoretical knowledge presented throughout the lectures in practice,
- motivating students to work systematically,
- developing students’ skills of individual and team work.
Throughout the classes the students will, individually or in groups, organize statistical data, select the methods for data analysis appropriate for specific purposes, determine statistical measures, interpret and critically evaluate the results of research. They will also present the results of their own statistical research.
Lectures + classes =60 hours
Self-study to prepare for lectures and classes = 90 hours
Preparation for tests/exams = 30 hours
Total: 180 hours
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Term 2023L:
not applicable |
Term 2024L:
not applicable |
Prerequisites (description)
Course coordinators
Learning outcomes
Upon completion of the course the student will:
KNOWLEDGE
1. have basic knowledge about sources of information about social problems and ways of obtaining and elaborating data about social problems;
2. know statistical terms and their classifications and the most important methods of statistical description;
3. know how to design and conduct a basic statistical analysis;
4. know how to describe reality based on the results of statistical analysis
SKILLS
1. be able to design and carry out a simple statistical analysis based on the available data
- be able to formulate a research problem and to translate it into a statistical survey objective;
- be able to select appropriate data to meet the research objective;
- deal with statistical data and present it ;
- select appropriate basic statistical methods and apply them;
- interpret the results of statistical research and critically respond to them.
2. be able to co-operate in a group
3. use a statistical package to present and analyse data
ATTITUDES:
1. appreciate the usefulness of statistical methods
2. appreciate the advantages of working in a team
3. understand the need to be honest when interpreting statistical data and research results
Assessment criteria
Prerquisites: The knowledge required to pass the Matura examination is sufficient to participate in the course. Computer, especially Excel, skills (e.g. classes in IT and Excel data management tools) will help to pass the course.
Final grade:
Active participation in classes: 40%
Written exam: 60%
Practical placement
not applicable
Bibliography
Mandatory:
1. Maksimowicz-Ajchel A., Wstęp do statystyki. Metody opisu statystycznego, Wydawnictwa Uniwersytetu Warszawskiego, Warszawa 2007.
Recomended:
1.E. Babbie, Badania społeczne w praktyce, Wydawnictwo naukowe PWN, Warszawa 2003.
2.Bielecka A. Statystyka w Biznesie i Ekonomii. Teoria i praktyka. Wydawnictwo Wyższej Szkoły Przedsiębiorczości i Zarządzania im. L. Koźmińskiego, Warszawa 2005.
3.Radhakrishna Rao C., Statystyka a prawda, PWN, Warszawa 1994.
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Term 2023L:
not applicable |
Term 2024L:
not applicable |
Notes
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Term 2023L:
not applicable |
Term 2024L:
not applicable |
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: