258-6 What's So Hard About Histograms?-

Session: Quantitative and Data Analysis Skills in Geoscience Education: Supporting Student, Course, and Program Outcomes (Posters)

Presenting Author:

Author:

Abstract:

Histograms are among the first steps we use to understand large datasets yet seem deceptively simple. One of the modules developed for The Math Your Earth Science Majors Need (TMYN-Majors) project is devoted entirely to histograms. When writing this module, it quickly became apparent that much of understanding a histogram frequency plot is based on the concept of probability distributions. Without this basis, students introduced to histograms might not be able to determine the construction parameters (bin size) that produce a "good" level of detail or how to address outliers. A further challenge in teaching with histograms is that they work best with large datasets and thus require a computer or spreadsheet to construct. This makes the process somewhat opaque to the novice. The module written for TMYN-Majors includes examples of histogram construction and interpretation using earth science datasets like streamflow measurements. The final section of the module explores how to graphically interpret basic statistics like mean, median, mode, and skew from histograms. Understanding the relationship of the frequency (count) to a percent to a probability is a step towards understanding and creating cumulative frequency plots like those used for return periods or grain size distributions.

Geological Society of America Abstracts with Program. Vol. 57, No. 6, 2025

© Copyright 2025 The Geological Society of America (GSA), all rights reserved.