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Descriptive Statistics

  • Marko Sarstedt
  • Erik Mooi
Chapter
  • 132k Downloads
Part of the Springer Texts in Business and Economics book series (STBE)

Abstract

We first provide an overview of market research’s workflow. We then discuss efficient strategies to help you structure your project’s database, as well as enter, clean, and easily check the collected data for inconsistencies. In addition, we provide easy strategies that allow you to handle missing data observations before we describe the most common and useful univariate and bivariate descriptive graphs and statistics. Thereafter, we take you through the basics of SPSS and provide useful tips on how to create and interpret descriptive statistics and table outputs. A range of graphs is illustrated and applied in SPSS, including bar charts, histograms, box plots, pie charts, frequency tables, scatter graphs, crosstabs, and correlation tables, all of which are useful for differently scaled variables. We make use of a case study for an easy and meaningful interpretation of the graphs and table outputs. We conclude with recommendations for further readings and a case study with review questions.

Keywords

Bivariate Description Missing Completely At Random (MCAR) Chart Builder MCAR Test Missing Not At Random (MNAR) 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Further Reading

  1. Huck, S. W. (2014). Reading statistics and research (6th ed.). Harlow: Pearson Education.Google Scholar
  2. Levesque, R., Programming and data management for IBM SPSS Statistics 20. Chicago, SPSS, Inc. Available at http://www.spsstools.net/en/resources/spss-programming-book/

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Marko Sarstedt
    • 1
  • Erik Mooi
    • 2
  1. 1.Faculty of Economics and ManagementOtto-von-Guericke- University MagdeburgMagdeburgGermany
  2. 2.Department of Management and MarketingThe University of MelbourneParkville, VICAustralia

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