Introduction Welcome to my Probabilistic Data Visualization project! Inspired by the work of Ferreira, Fisher, and Konig (2014), I set out to address the challenges users face when interpreting bar charts with confidence intervals. In this project, I've implemented an advanced bar coloring technique that provides users with a nuanced understanding of the distribution of data points around a given y-axis value.
Project Objective The primary goal of this project is to enhance users' ability to make informed decisions about probabilistic data represented in bar charts. By implementing a sophisticated coloring scheme based on the data covered, users can visually assess the likelihood of x-axis values relative to a specified y-axis value.
Implementation Details Bar Coloring Technique I have chosen the harder option, wherein the color of each bar is determined by the amount of data covered. The color gradient ranges from dark blue (indicating the distribution is certainly below the y-axis value) to white (representing certainty that the value is contained within the distribution) to dark red (suggesting the value is certainly not contained as the distribution is above the axis).
Usage Run the code to generate the bar chart visualization.
Conclusion
This Probabilistic Data Visualization project aims to empower users to make better decisions when interpreting bar charts with confidence intervals. Combining an advanced coloring scheme and interactivity enhances the user experience, providing a deeper understanding of the underlying probabilistic data.
Output
