SOCR News IASE Distributome 2021

SOCR News & Events: Probability Distributome – Computing, Visualization, and Instruction

SOCR Resource

SOCR.

Logistics

• 2021 IASE Conference on Statistics Education in the Era of Data Science (Distance/virtual event)
• Dates/Times: August 30 – September 4, 2021 (Time TBD)
• Registration: Participants have to register to attend in advance (Per ISI/IASE registration for students is free)
• Program: Program
• Title: Probability Distributome – Computing, Visualization, and Instruction
• Authors: Jared Tianyi Chai, Mark Bobrovnikov, and Ivo Dinov, SOCR, University of Michigan.

Abstract

The concept of a probability distribution is in the core of all modern data-driven modeling, simulation, analytics, inference, prediction, and prognostication of observable natural phenomena. Despite the large number of possible probability distributions and their significant heterogeneity, dozens of distributions are named and well understood, many are interconnected, and all of them span the universe of possible physical processes. This manuscript reports on the probability Distributome, which allows navigation, exploration and learning of many univariate distributions, and facilitate the computation and visualization associated with univariate, bivariate and trivariate probability distributions. We illustrate applications of three specific resources including an HTML5/JavaScript applications (Distributome), RShiny apps and and 3D plotly apps. These resources are freely accessible, open-source, and platform agnostic. Both learners and instructors may utilize, expand, improve, and customize these tools for their specific research and education needs.

Background

• SOCR News & Events
• SOCR Global Users
• SOCR Navigators
• SOCR Datasets and Challenging Case-studies
• Electronic Textbooks:
  • Probability and Statistics EBook
  • Scientific Methods for Health Sciences
  • Data Science and Predictive Analytics

• Spacekime website
• Time-Complexity and Inferential Uncertainty (TCIU)

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References

• This work is sponsored in part by NIH Grants P30 DK089503, P20 NR015331, R01CA233487, and R01MH121079, as well as, NSF Grants 1916425, 1734853 and 1636840.
• SOCR Home page: https://www.socr.umich.edu

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