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Data, Models, and Software

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Discrete Choice Analysis with R

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

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Abstract

Models propose a simplified representation of the reality, which is useful to develop a common ground for describing, analyzing, and understanding complex phenomena. Model building requires three things: Raw materials. Tools. Technical expertise (hopefully!). This is true whether the model is physical (for instance a sculpture), conceptual (a mental map), or statistical/mathematical (the gravity model or a regression model). In the case of a sculpture, the raw materials can be marble, wood, or clay; the tools chisels, mallet, and spatula; and the technique the mastery of the sculptor when working with the tools and the materials. Anyone can try sculpture, and most people can create sculptures.

“You can have data without information, but you cannot have information without data.”

Daniel Keys Moran

“Essentially, all models are wrong, but some are useful.”

George E.P. Box

“All models are wrong but some I am emotionally attached to.”

Isabella Bicalho-Frazeto

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Notes

  1. 1.

    Notebooks are a form literate programming (see https://en.wikipedia.org/wiki/Literate_programming) a style of document that uses code to illustrate a discussion, as opposed to the traditional programming style that uses natural language to discuss/document the code. It flips around the usual technical writing approach to make it more intuitive and accessible.

  2. 2.

    https://www.merriam-webster.com/dictionary/data.

  3. 3.

    https://en.wikipedia.org/wiki/Likert_scale.

  4. 4.

    https://cran.r-project.org/web/packages/cluster/index.html.

  5. 5.

    https://cran.r-project.org/web/packages/ggplot2/index.html.

  6. 6.

    https://cran.r-project.org/web/packages/dplyr/.

  7. 7.

    https://cran.r-project.org/.

  8. 8.

    https://dplyr.tidyverse.org/.

  9. 9.

    https://ggplot2-book.org/.

  10. 10.

    https://raw.githubusercontent.com/rstudio/cheatsheets/main/data-visualization.pdf.

References

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  • Ortúzar, J. D., & Willumsen, L. G. (2011). Modelling transport (4th ed.). New York: Wiley.

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  • Tukey, J. W. (1977). Exploratory Data Analysis. Reading, Massachussets: Addison-Wesley Publishing Company.

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  • Whalen, K. E., Páez, A., & Carrasco, J. A. (2013). Mode choice of university students commuting to school and the role of active travel. Journal of Transport Geography, 31, 132–42. https://doi.org/10.1016/j.jtrangeo.2013.06.008.

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Correspondence to Antonio Páez .

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Páez, A., Boisjoly, G. (2022). Data, Models, and Software. In: Discrete Choice Analysis with R. Use R!. Springer, Cham. https://doi.org/10.1007/978-3-031-20719-8_1

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