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This chapter highlights the importance of data exploration as a preliminary step in building choice models. By examining choice patterns and uncovering key influencing factors, you can establish a solid basis for the subsequent model development. This initial step involves a series of exploratory data analysis techniques that are simple yet informative. In this chapter, we demonstrate how to use R to effectively conduct this exploration, transforming raw data into meaningful insights. By creating summary tables and examining data visualisations, researchers can gain a deeper understanding of their data, paving the way for a more effective analysis and model building.

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From Raw Data to Insights

  • 章节

  • 出版模式：

    开放获取

  • 发表日期：

    2025年

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  • Petr Mariel,
  • Danny Campbell,
  • Erlend Dancke Sandorf,
  • Jürgen Meyerhoff,
  • Ainhoa Vega-Bayo,
  • Rebecca Blevins

摘要

This chapter highlights the importance of data exploration as a preliminary step in building choice models. By examining choice patterns and uncovering key influencing factors, you can establish a solid basis for the subsequent model development. This initial step involves a series of exploratory data analysis techniques that are simple yet informative. In this chapter, we demonstrate how to use R to effectively conduct this exploration, transforming raw data into meaningful insights. By creating summary tables and examining data visualisations, researchers can gain a deeper understanding of their data, paving the way for a more effective analysis and model building.