Hypothetical Outcome Plots Outperform Error Bars and Violin Plots for Inferences about Reliability of Variable Ordering
نویسندگان
چکیده
Many visual depictions of probability distributions, such as error bars, are difficult for users to accurately interpret. We present and study an alternative representation, Hypothetical Outcome Plots (HOPs), that animates a finite set of individual draws. In contrast to the statistical background required to interpret many static representations of distributions, HOPs require relatively little background knowledge to interpret. Instead, HOPs enables viewers to infer properties of the distribution using mental processes like counting and integration. We conducted an experiment comparing HOPs to error bars and violin plots. With HOPs, people made much more accurate judgments about plots of two and three quantities. Accuracy was similar with all three representations for most questions about distributions of a single quantity.
منابع مشابه
Poincaré Plots for Residual Analysis
After some suitable ordering of the residuals, et, t = 1, . . . , n, it is suggested that scatter plots of et+1 vs. et along with a robust smooth loess trend be routinely examined to check for lack of statistical independence. Such plots may be termed Poincaré plots because of their similarity to plots used in nonlinear dynamical systems. Poincaré plots are helpful in detecting positive correla...
متن کاملHierarchical Pixel Bar Charts
Simple presentation graphics are intuitive and easy-to-use, but only show highly aggregated data. Bar charts, for example, only show a rather small number of data values and x-y-plots often have a high degree of overlap. Presentation techniques are often chosen depending on the considered data type—bar charts, for example, are used for categorical data and x-y plots are used for numerical data....
متن کاملSinaPlot: an enhanced chart for simple and truthful representation of single observations over multiple classes
Abstract Recent developments in data driven science, in particular computational biology, have led scientists to integrate data from several sources, over diverse experimental procedures, or databases. This alone poses a major challenge in truthfully visualising data, especially when the amount of data points varies between classes. To aid the presentation of datasets with differing sample size...
متن کاملRepresenting uncertainty on model analysis plots
Model analysis provides a mechanism for representing student learning as measured by standard multiple-choice surveys. The model plot contains information regarding both how likely students in a particular class are to choose the correct answer and how likely they are to choose an answer consistent with a well-documented conceptual model. Unfortunately, Bao’s original presentation of the model ...
متن کاملeAppendix 1: Lasagna plots: A saucy alternative to spaghetti plots
Longitudinal repeated-measures data have often been visualized with spaghetti plots for continuous outcomes. For large datasets, the use of spaghetti plots often leads to the over-plotting and consequential obscuring of trends in the data. This obscuring of trends is primarily due to overlapping of trajectories. Here, we suggest a framework called lasagna plotting that constrains the subject-sp...
متن کامل