Publications by R. Paul Wiegand

W4: General Principles, Axes, and Baselines

22.05.2020

Spring 2020 Outline Clarity of Data Trellis Displays Clarity of Plot Elements Clarity of Understanding Scales & Axes Summary of Principles Clarity of Data Emphasize Data Good plots should: Make the data stand out Make it easy for the reader to decode the data Avoid unnecessary “chart junk” Use large enough plot elements to see and disting...

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R3-GGPlot

15.05.2020

Spring 2020 Outline GGPlot2 Overview GGPlot2 Layers and Examples Colors in GGPlot2 More Examples More Information GGPlot2 Overview Why ggplot2? The ggplot2 library: uses a consistent grammar of graphics provides a high-level plots specification allows user to think in terms of a layers data visualization pipeline provides extensive visualizat...

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W3: Simple Effective Graphs, Interaction & Navigation

14.05.2020

Summer 2020 Outline Plotting Tools Visualizing Single Variate Distributions & Values Visualizing Multi-Variate Distributions & Values Interaction & Navigation Analytical Navigation Further Help Plotting Tools Out-of-the-Box Tools Microsoft Excel Google Spreadsheet Many Eyes Tableau SPSS Some Programming Required Python PHP, HTML, Javascript...

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W1: Introfuction to Data visualization

11.05.2020

Summer 2020 Outline Course orientation Statistics Review Terminology & Concepts History of Visualization Traits of Meaningful Data Effective Graphing Limitations in Data Visualization Course Orientation Course Objective This course: Provides an interdisciplinary introduction to the principles and fundamentals of visualizing statistical inform...

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W2: Perception & Representations

11.05.2020

Summer 2020 Outline Graphical Perception Tasks Encoding Numeric Data, Proportions, Frequencies Encoding Categorical Distinctions Abstraction & Cognitive Considerations Design Principles Clutter Gathering Data Storing & Formatting Data Graphical Perception Tasks The Visual Perception System Eyes sense light reflecting & refracting off of surfa...

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R1: Introduction to R

11.05.2020

Summer 2020 Why Are We Using R? R is open source and freely available Works on all standard platforms (Mac, Windows, linux) Standard tool for many sciences (e.g., Computer Science, Physics) Easy to produce web-based slides using: R-Studio R-Markdown Traditional statistics tool with GUI front ends, as well as a flexible and powerful programmin...

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R2: Handling Data

11.05.2020

Spring 2020 Outline Manipulating Data in R R Models Manipulating Data in R Common Manipulation Needs Robust file reading options read.table() has a lot features Select only a certain subset of variables or observations subset(), filtering data, and slicing data Summarize or combine data aggregate() and joining data Reorder data sets bas...

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COVID-19 Deaths Are Not Media Hype

01.05.2020

There are a lot people in the US that believe that the mortality rate of COVID-19 is far lower than reported. It is understandable; we are suffering significant economic damage as a result of the policies we’ve put in place to mitigate the health risks. Unemployment rates are skyrocketting, businesses are going under, the entire US economy is b...

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W7b: Visualizing and Analyzing Time

17.06.2020

Summer 2020 Outline What to look for in time Discrete data over time Continuous data over time Issues with plotting cycles What to Look for Where the Focus is Yau says, when visualizing patterns over time, we typically focus on: Illustrating (dramatic) changes Describing general trends Describing some periodic pattern Making implicit and expl...

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W8: Visualizing and Analyzing Differences & Deviations

17.06.2020

Summer 2020 Outline Multivariate Comparisons Standard Statistical Dimension Reduction Clustering Searching for Outliers More Example Code! Multivariate Comparisons Heatmaps Heat maps are a 2D matrix of data, where values are displayed as colored shapes in the matrix Typically this is a rectangular grid, and: Rows correspond to an observation...

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