Furniture for Quantitative Scientists

Abstract:

A basic understanding of the distributions of study variables and the relationships among them is essential to inform statistical modeling. This understanding is achieved through the com putation of summary statistics and exploratory data analysis. Unfortunately, this step tends to be under-emphasized in the research process, in part because of the often tedious nature of thorough exploratory data analysis. The table1() function in the furniture package streamlines much of the exploratory data analysis process, making the computation and communication of summary statistics simple and beautiful while offering significant time-savings to the researcher.

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Authors

Affiliations

Tyson S. Barrett

 

Emily Brignone

 

Published

July 23, 2017

Received

Dec 23, 2016

DOI

10.32614/RJ-2017-037

Volume

Pages

9/2

142 - 148

CRAN packages used

furniture

CRAN Task Views implied by cited packages

Footnotes

    Reuse

    Text and figures are licensed under Creative Commons Attribution CC BY 4.0. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".

    Citation

    For attribution, please cite this work as

    Barrett & Brignone, "The R Journal: Furniture for Quantitative Scientists", The R Journal, 2017

    BibTeX citation

    @article{RJ-2017-037,
      author = {Barrett, Tyson S. and Brignone, Emily},
      title = {The R Journal: Furniture for Quantitative Scientists},
      journal = {The R Journal},
      year = {2017},
      note = {https://doi.org/10.32614/RJ-2017-037},
      doi = {10.32614/RJ-2017-037},
      volume = {9},
      issue = {2},
      issn = {2073-4859},
      pages = {142-148}
    }