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Introduction and Descriptive Statistics

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Understanding Inferential Statistics

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Abstract

Progress in many scientific disciplines builds on creative ideas and questions that can only be answered on the basis of empirical data. Similarly, predictions from theories can only be tested using empirical data. In this context, scientific work often claims to uncover universally valid regularities about causal mechanisms or relationships between different variables. Inferential statistics provides a framework on how to arrive at such conclusions. This chapter provides a short overview of the aim of inferential statistics, combined with condensed information on relevant basics from descriptive statistics.

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Notes

  1. 1.

    There are different notations for the arithmetic mean; we use \(\bar {X}\) and MX interchangeably.

  2. 2.

    Some textbooks define the variance slightly differently and divide not by n, but by n − 1. When computing descriptive statistics of a sample, however, we should use the version introduced here; in Sect. 3.4 we will clarify this difference.

  3. 3.

    Clicking Paste instead of OK will convert the requested operation to syntax that can be saved and re-run later on.

References

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Authors and Affiliations

  1. Research Methods and Cognitive Psychology, University of Bremen, Bremen, Germany

    Markus Janczyk

  2. General Psychology, Trier University, Trier, Germany

    Roland Pfister

Authors
  1. Markus Janczyk
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  2. Roland Pfister
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Janczyk, M., Pfister, R. (2023). Introduction and Descriptive Statistics. In: Understanding Inferential Statistics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-66786-6_1

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