B_ZKA Introduction to Analysis of Data from Sociological Surveys using SPSS

University of Finance and Administration
Summer 2015
Extent and Intensity
2/2. 5 credit(s). Type of Completion: zk (examination).
Guaranteed by
prof. PhDr. Petr Matějů, Ph.D.
Subdepartment of Management and Marketing – Department of Economics and Management – Departments – University of Finance and Administration
Contact Person: Ivana Plačková
Prerequisites
There are no prerequisites for this course.
Course Enrolment Limitations
The course is offered to students of any study field.
Course objectives
One of the goals of the course is to alleviate fear of data analysis, so typical among students of sociology. The successful course graduate will be able to understand and correctly interpret the results of elementary statistical analysis of data from sociological surveys. To achieve this goal, students will be guided to translate elementary research questions into analytical ones, to understand the structure and the role of survey data as well as the basic rules for the selection of appropriate method and statistical procedure with respect to types of variables analyzed (interval, continuous, ordinal, nominal), their distributions (normal, poisson, binomial, etc.) and hypotheses to be tested. In seminars students will be guided to run basic statistical procedures in SPSS (Statistical Package for the Social Sciences). The survey data for the course will be provided by the instructor. Working with real data, students will learn and practice how to modify (transform) existing variables, create new variables and, finally, to run elementary one- and two-dimensional statistical analyses, and present and interpret their results.
Syllabus
  • 1.Principal characteristics of sociological survey data, structure of data file and its appearance in SPSS. Types of hypotheses, elementary rules for the formulation of hypotheses and their testing on survey data.
  • 2. Introduction to data file documentations from surveys to be used during the course (ISSP 2009 Inequality, PISA 2003, EUROSTUDENT-CZ). Data file documentations questionnaires and codebooks) will be accessible through the Information system (Study materials). How to assess the content and structure of data file (procedure DISPLAY).
  • 3. Types of variable (nominal, ordinal, continuous), basic rules the choice of right statistical procedure appropriate to types of variables to be analyzed.
  • 4. Introduction to statistical package SPSS (version 19), basic operations with files, (data files, syntax file, output file), elementary rules for running SPSS through pop-up menus as well as SPSS syntax (which will be preferred).
  • 5. Distributions of nominal and ordinal variables, their principal characteristics. Practicing procedures providing main characteristics of nominal and ordinal variables, generating simple tables and graphs (FREQUENCIES, EXPLORE).
  • 6. Distributions of continuous variables, their principal characteristics. Practicing procedures providing main characteristics (moments) of distributions of continuous variables, generating simple tables and graphs for continuous variables (DESCRIPTIVES, EXPLORE, MEANS).
  • 7. Transformations of variables, basic principles of generating new variables (COMPUTE, COUNT), recoding existing variables (RECODE), handling missing values. Selecting specific cases (subsamples) for analyses (SELECT IF).
  • 8. Normal distribution, its main properties, principles of hypotheses testing based on normal distribution, population and samples, types of samples, statistical inference.
  • 9. Comparing samples and subsamples, analyses and testing of means (T-TEST).
  • 10. Principles of analyses based on categorical (nominal, ordinal) variables, crosstabulations, right choice among measures of association for different types of variables (CROSSTABS).
  • 11. Principles of analyses of variance, components of variance (total, between groups, within groups), comparing groups testing hypotheses about equality of means using analysis of variance (procedures ONEWAY and ANOVA).
  • 12. Principles of analyses of associations between continuous variables (covariance, correlations) procedure CORRELATIONS. How to assess other than linear associations between variables with non-normal distributions (NONPAR CORR). The effect of a third variable and how to identify it (partial correlation) procedure (PARTIAL CORR).
  • .
Literature
    required literature
  • Dotazníky a „codebooks“ datových souborů ze sociologických výzkumů používaných pro výuku a procvičování (ISSP 2009, PISA 2003, EUROSTUDENT 2009).
  • Pallant, J.: SPSS Survival Manual: A step by step guide to data analysis using SPSS. Open University Press, 2010.
  • Collier, J. Using SPSS Syntax: A Beginner's Guide. Sage Publications, 2009.
  • Průběžně připravované prezentace vyučujícího
    recommended literature
  • IBM SPSS. SPSS Statistics Base 19. SPSS 1989, 2010.
  • SPSS. SPSS Base 16.0. Grafika. Praha, Centrum výuky SPSS. 2008
  • Bryman, A., C. Cramer: Quantitative Data Analysis with IBM SPSS 17, 18 & 19: A Guide for Social Scientists. Routledge, 2011.
  • IBM SPSS. SPSS Statistics 19 Command Syntax Reference. SPSS 1989, 2010
  • Rabušic, L. a P. Mareš: Materiál pro kurs Statistická analýza dat pomocí SPSS. Brno, FSS MU. 2010. (3 výtisky budou uloženy na katedře sociologie).
  • SPSS. SPSS Base 16.0. Datový soubor a práce s výstupy. Praha, Centrum výuky SPSS. 2008
    not specified
  • SPSS. SPSS Base 16.0. Statistické procedury. Praha, Centrum výuky SPSS. 2008
Teaching methods
Lectures and seminars in full-time study, tutorials in part-time study; compulsory seminar participation is 75% in full-time study, compulsory tutorial participation is 50% in part-time study. Every topic will be covered by a lecture and a seminar. Lectures will be based on presentations of individual topics by the lecturer followed by a discussion. Seminars will be based on presentations of assignments prepared by the students (usually 2 presentations per seminar, each about 20 minutes long, followed by a discussion). Presentations will draw primarily on assigned analyses performed on the survey data provided by the instructor. Every student must sign up for at least 2 seminar presentations to be eligible to submit a final paper.
Assessment methods
a) To get a credit (which is a pre-requisite for the oral examination) student is required:
1. To attend seminars (min. 75 %) and present there at least two times the results of assigned analyses.
2. To pass the final test assessing capability to run assigned analyses and interpreting their results.
b) To pass the examination student will be required to submit in a due time a course final paper on the selected topic (list of topics will be provided by the instructor at the end of the semester). The paper will answer the analytical questions. Students will choose analytical tools (statistical procedures) to answer the questions (the appropriateness of the chosen procedure will the main be part of the paper evaluation), run the analysis, present and interpret the results. The paper will consist of:
a. Discussion of the method (SPSS procedure) chosen for the analysis (why the particular procedure was chosen).
b. Tables and/or graphs presenting the main results (selected results answering analytical questions).
c. Interpretation of results.
d. Appendix 1: A complete SPSS syntax for the performed analyses.
e. Appendix 2: A complete SPSS outputs from the analyses.
Language of instruction
Czech
Further comments (probably available only in Czech)
The course can also be completed outside the examination period.
General note: Aa1.
The course is also listed under the following terms summer 2012, Summer 2013, Summer 2014.
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