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Describing Data

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R for Marketing Research and Analytics

Part of the book series: Use R! ((USE R))

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Abstract

In this chapter, we tackle our first marketing analytics problem: summarizing and exploring a data set with descriptive statistics (mean, standard deviation, and so forth) and visualization methods. Such investigation is the simplest analysis one can do yet also the most crucial. It is important to describe and explore any data set before moving on to more complex analysis. This chapter will build your R skills and provide a set of tools for exploring your own data.

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References

  1. Chang, W. (2012). R graphics cookbook. Sebastopol: O’Reilly Media.

    Google Scholar 

  2. Fox, J., & Weisberg, S. (2011). An R companion to applied regression (2nd ed.). Thousand Oaks: Sage. http://socserv.socsci.mcmaster.ca/jfox/Books/Companion.

  3. Kahle, D., & Wickham, H. (2013). ggmap: A package for spatial visualization with Google Maps and OpenStreetMap. http://CRAN.R-project.org/package=ggmap, R package version 2.3.

  4. Knuth, D. (1997). The art of computer programming, Vol. 2: Seminumerical Algorithms (3rd ed.). Reading: Addison-Wesley.

    Google Scholar 

  5. Neuwirth, E. (2011). RColorBrewer: ColorBrewer palettes. http://CRAN.R-project.org/package=RColorBrewer, R package version 1.0-5.

  6. Revelle, W. (2013). psych: Procedures for psychological, psychometric, and personality research. Evanston: Northwestern University. http://CRAN.R-project.org/package=psych, R package version 1.3.10.

  7. Sarkar, D. (2008). Lattice: Multivariate data visualization with R. New York: Springer.

    Google Scholar 

  8. South, A. (2011). rworldmap: a new R package for mapping global data. The R Journal, 3(1), 35–43. http://journal.r-project.org/archive/2011-1/RJournal_2011-1_South.pdf.

  9. Wickham, H. (2009). ggplot2: Elegant graphics for data analysis. New York: Springer.

    Google Scholar 

  10. Wong, D. M. (2010). The wall street journal guide to information graphics: The Dos and Don’ts of presenting data, facts, and figures. New York: WW Norton & Company.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Google, Inc., Seattle, WA, USA

    Chris Chapman

  2. LeBow College of Business, Drexel University, Philadelphia, PA, USA

    Elea McDonnell Feit

Authors
  1. Chris Chapman
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  2. Elea McDonnell Feit
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Corresponding author

Correspondence to Chris Chapman .

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© 2015 Springer International Publishing Switzerland

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Chapman, C., Feit, E.M. (2015). Describing Data. In: R for Marketing Research and Analytics. Use R!. Springer, Cham. https://doi.org/10.1007/978-3-319-14436-8_3

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