Small Multiples: Unlocking the Power of Data Vis. With Edward Tufte - Essay Sample

Introduction

Edward Tufte introduced small multiples used in statistics. The ultimate goal of small multiple was to describe the arrangement of small graphs with the same and consistent quantitative scale. However, every small graph showed a different subset of a broader set of data. The multiple small arrangements permit a person to add another variable to the first variable into a multivariate one without interfering with the visibility. Arranging the small multiples as a cross tab allows the graph to display more multivariate variables. Colors can be assigned to the bar to ensure there is clarity ("http://www.perceptualedge.com/articles/b-eye/visual_multivariate_analysis.pdf," n.d.).

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Multiple Concurrent Views With Brushing Functionality

Multiple concurrent views with brushing functionality is a multivariate approach that deals with the ability to place many different aspects of the same data set, such as tables and multiple graphs. Thus, it allows the user to select a subset of the data in one of the graphs. The highlighted subset appears on the individual view. The clarity gives a powerful option to assess connections between multiple variables. The margin of the variables may be correlated in the form of a scatterplot. The low margin of a variable may be reasonably consistent ("http://www.perceptualedge.com/articles/b-eye/visual_multivariate_analysis.pdf," n.d.).

Heat Map Matrix

The heat map is any visual display that applies color variations to encode quantitative variables. For instance, the weather map uses color to encode precipitation or temperature variation. A heat map matrix takes the shape of the tabular arrangement of cells. Each matrix encodes a quantitative variable as the color corresponds to the categorical values down the rows and other categorical variables across the columns. Heat Matrix can be used to analyze sales in terms of ranges. In a heat matrix, more variables can be added from a strict arrangement of the crosstab. Thus, it is achieved by placing a different variable in every column. For that reason, it makes every column to represent a different variable. In a heat map matrix, every column uses a different color to encode is quantitative values. The scale used is different because of the uniqueness of the set of values ("http://www.perceptualedge.com/articles/b-eye/visual_multivariate_analysis.pdf," n.d.).

Parallel Coordinates

Parallel coordinates is the newest visualization used in statistics. Scientists mostly use parallel coordinates. They seem to meaningless and absurd clutter of lines. The lines form a separate entity, which is each line running from the left to the right across the plot area. A different variable is given when each vertical axis which is evenly spaced across left to right of the plot area. The power of real coordinates is reached when there is an interaction with the display to filter out what does not interest a person to allow the user to find entities that align to a specific multivariate profile that interests the user ("http://www.perceptualedge.com/articles/b-eye/visual_multivariate_analysis.pdf," n.d.).

Glyphs

A glyph is a graphical object that represents multiple variables' values simultaneously. The glyph is complex and can surpass the meaning displayed. Designing a glyph requires correct multivariate data. Besides, glyph should be used appropriately. In monitoring particular patterns of interest and a large set of data for irregularities, glyphs can be used to paint a useful picture. For instance, constructing a stay glyph, a person should start withdrawing a radial axes arrangement that proceeds from a common center to form a circle. Every axis should give a separate variable with high values close to the perimeter and low values near the center ("http://www.perceptualedge.com/articles/b-eye/visual_multivariate_analysis.pdf," n.d.).

References

http://www.perceptualedge.com/articles/b-eye/visual_multivariate_analysis.pdf. (n.d.).