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2: Describing Data using Distributions and Graphs

  • Page ID
    42002
    • Linda R. Cote, Rupa G. Gordon, Chrislyn E. Randell, Judy Schmitt, and Helena Marvin
    • University of Missouri System

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    • 2.1: Graphing Qualitative Variables
      This page emphasizes the significance of using visual tools like tables and graphs for data interpretation, particularly in analyzing iMac buyers' prior computer ownership. It advocates for using bar charts over pie charts for better comparisons across categories while cautioning against misleading graphical practices. The text provides resources for recognizing inappropriate graphing techniques and stresses the need for clarity and accuracy in data visualization.
    • 2.2: Graphing Quantitative Variables
      This page describes various methods for visualizing quantitative data distributions, including stem-and-leaf displays, histograms, frequency polygons, box plots, bar charts, and line graphs. It highlights their effectiveness in representing data shapes, skewness, and comparisons: stem-and-leaf displays are compact and suited for small datasets, histograms group larger datasets, and box plots show ranges and outliers.


    This page titled 2: Describing Data using Distributions and Graphs is shared under a CC BY-NC-SA 4.0 license and was authored, remixed, and/or curated by Linda R. Cote, Rupa G. Gordon, Chrislyn E. Randell, Judy Schmitt, and Helena Marvin via source content that was edited to the style and standards of the LibreTexts platform.