Basic Survey Data Analysis

  • Seppo Laaksonen


This chapter includes basic survey data analysis, such as estimating frequencies, means, and statistical models, using ‘survey instruments’ but not going into most complex cases. The purpose is to give instructions for survey analysis using general statistical software, such as SAS, SPSS, STATA, or R, but without details about them. Examples using PISA and ESS are the main part here, some being derived from ESS-related test data as well (see Sect.  6.1). The chapter is primarily based on these examples. They do not cover complex samples, but such can be rather straightforwardly calculated using one of the software packages. The SAS, SPSS, STATA, or R software work well with the following sampling designs in cross-sectional surveys:
  • Simple or stratified random sampling

  • Equidistance sampling, assuming that it corresponds to simple random sampling

  • Unstratified or stratified two-stage cluster sampling


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  3. Lumley, T. (2010). Complex surveys: A guide to analysis using R, Series in survey methodology. New York: Wiley.CrossRefGoogle Scholar
  4. Martela, F., & Steger, M. F. (2016). The three meanings of meaning in life: Distinguishing coherence, purpose, and significance. The Journal of Positive Psychology, 11(5), 531–545.CrossRefGoogle Scholar
  5. PISA. (2015). PISA, Questionnaire framework. Retrieved January 2017, from

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Seppo Laaksonen
    • 1
  1. 1.Social Research, StatisticsUniversity of HelsinkiHelsinkiFinland

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