Descriptive Statistics

Marko Sarstedt and Erik Mooi
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Marko Sarstedt: Otto-von-Guericke- University Magdeburg
Erik Mooi: The University of Melbourne

Chapter 5 in A Concise Guide to Market Research, 2019, pp 91-150 from Springer

Abstract: 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) (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sptchp:978-3-662-56707-4_5

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DOI: 10.1007/978-3-662-56707-4_5

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