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Descriptive Statistics

In: Basic Principles of Applied Medical Statistics

Author

Listed:
  • Jos W. R. Twisk

    (Amsterdam UMC, Department of Epidemiology and Data Science)

Abstract

Descriptive statistics are used to describe a study population. In this chapter it is shown that different statistics are used for continuous variables and for dichotomous or categorical variables. Furthermore, a distinction can be made between numerical descriptives and graphical descriptives. Numerical descriptives are, for example, the mean, median and measures to describe the spread in the data, such as the standard deviation. Graphical descriptives are, for example, a histogram and a stem-and-leaf plot.

Suggested Citation

  • Jos W. R. Twisk, 2025. "Descriptive Statistics," Springer Books, in: Basic Principles of Applied Medical Statistics, chapter 0, pages 7-15, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-86278-6_2
    DOI: 10.1007/978-3-031-86278-6_2
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    Citations

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    Cited by:

    1. Hana Urbánková & Jana Stávková, 2025. "The Context of Sustainability and Generational Differences in Consumer Behaviour," European Journal of Business Science and Technology, Mendel University in Brno, Faculty of Business and Economics, vol. 11(2), pages 206-219.
    2. Jahanshahi, Danial & Costello, Seósamh B. & Dirks, Kim Natasha & van Wee, Bert, 2025. "Biking and belonging: understanding the role of socio-cultural influences on cycling in Auckland," Transportation Research Part A: Policy and Practice, Elsevier, vol. 199(C).
    3. Olli Kurkela & Saara Metso & Leena Forma & Kimmo Suokas & Pekka Rissanen & Jaakko Nevalainen, 2026. "Productivity costs of type 2 diabetes with or without co-occurring substance use disorder and depression," Health Economics Review, Springer, vol. 16(1), pages 1-11, December.
    4. Pejić Sonja & Tomašević Ana Nešić, 2025. "Foreign direct investment and technology transfer: unlocking Serbia’s growth potential," Engineering Management in Production and Services, Sciendo, vol. 17(3), pages 101-112.
    5. Gril, Lorena & Rendtel, Ulrich, 2026. "Mapping high-income taxpayers in Berlin using kernel-smoothed proportions from aggregated georeferenced data," Discussion Papers 2026/2, Free University Berlin, School of Business & Economics.

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