Section outline

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    BADGE – Becoming a Digital Global Engineer

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    Badge

    Intellectual Output

    cc logo

    BADGE – Becoming a Digital Global Engineer
    Project 2019-1-FR01-KA203-063010 (167 512 512)

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    Objectives

    presentation

    • After studying this unit, you will be able to …

      1. define a scatter plot, a bubble chart, an area chart, a gauge chart, a funnel chart and a radar chart;

      2. use the above types to represent graphical data effectively;

      3. choose from a range of basic or more sophisticated types of graphical representation to make your presentation, dissertation or papers more detailed but, at the same time, clearer for your audience.

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    Warm up questions

    questions

      1. How can data be represented graphically?

      2. What kinds of graphical representation do you use to visualize data?

      3. Do you know what the differences and similarities are between the following types of graphical representation?

        • a scatter plot
        • a bubble chart
        • an area chart
        • a gauge chart
        • a funnel chart
        • a radar chart
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    Did you know?

    • The use of statistical graphics did not proliferate in Playfair’s lifetime—he died in 1823. But by the beginning of the 20th century, graphical representations of data were common in textbooks and used by governments, financiers, and scientists. Both the French and American governments annually published statistical atlases filled with charts that aimed to explain the world.

      Yet charts were nowhere to be seen in the newspaper. There were lots of statistics in the paper. Journalists wrote about trends in the bond markets, activity in the commodity markets, and changing birth rates. Numbers were a big part of the media; they just weren’t visualized.”

      Adapted from Priceonomics by Dan Kopf, Sep 14, 2016

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    Reading

    • There is a wide spectrum of data presentation tools, one of which is the scatter plot. This typically displays values for two variables for a set of data. The dots on the scatter plot represent data points. Scatter plots are used with variable data to study possible relationships between different variables. Even though a scatter plot depicts a relationship between variables, it does not indicate a cause-and-effect relationship. The aim of this tool is to determine what happens to one variable when the value of another variable changes. Scatter plots are used, for instance, to visually determine whether a potential relationship exists between an input and an outcome.

      Like the scatter plot, a bubble chart is primarily used to depict and show relationships between numeric variables. However, the addition of marker size as a dimension allows for a comparison between three variables rather than just two. Thus, a bubble chart is an extension of the scatter plot and is used to look at relationships between three numeric variables. Each dot in a bubble chart corresponds with a single data point, and the values of the variables for each point are indicated by its position horizontally and vertically, and the size of the dot.

      It is not only in scientific research that data is presented on a plane, but also in many other branches of everyday life. An area chart is the next example of how quantitative data can be presented and displayed. Area charts are used to represent cumulative totals using numbers or percentages or show trends over time among related attributes. When multiple attributes are included, the first attribute is plotted as a line and the area below it is shaded or filled with color. This is followed by the second attribute, and so on.

      Data representations are commonly used in many different areas of research but there are also ones which seem to be particularly dedicated to specific jobs. A tool which seems to be quite interesting especially in engineering, customer service, business, and quite often medicine, is a gauge chart. This type of chart can, for example, be a useful tool to measure customer satisfaction. In engineering, aircraft pilots regularly use gauge charts (Boeing and Airbus have conducted extensive research in this area, and their "glass cockpit" is still mainly made up of circular and half-circular gauges). On the other hand, medicine also uses gauge charts, but linear ones (called thermometers). A gauge chart uses needles to show information as a reading on a dial. Gauge charts are useful for comparing values between a small number of variables either by using multiple needles on the same gauge or by using multiple gauges. A gauge chart shows much more than one value. It gives the minimum, the maximum, and the current value, showing at lightning speed how far from the maximum you are.

      As we are now looking at data presentation tools dedicated to particular sectors, let us turn to the funnel chart. This one is a specialized chart type that demonstrates the flow of users through a business or sales process. The chart takes its name from its shape, which starts from a broad head and ends in a narrow neck. The number of users at each stage of the process are indicated by the funnel’s width as it narrows. Funnel charts are most often seen in business or sales contexts, where we need to track how a starting set of visitors or users drop out of a process or flow. This chart type shows how the starting whole breaks down into progressive parts.

      All the data presentation tools listed so far have been one-dimensional and thus depicted on a plane. A 2D chart, known as a radar chart, presents multivariate data by giving each variable an axis and plotting the data as a polygonal shape over all axes. All axes have the same origin, and the relative position and angle of the axes are usually not informative. The equiangular spokes, from the origin to the point on each axis represented by the variable, are called radii. A radar chart is often a good choice if you need to plot a series of observations or cases with multivariate data. Each observation or case is represented by a polygon and if they are shaded opaquely, it is easy to see how they overlap and in which direction. A radar chart is especially useful if you want to compare the general shape, reach and symmetry of the distribution of variables rather than specific quantities among observations. Moreover, it is ideal if you are working with a large number of variables or if you want a quick visual way of viewing data.

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    Activities

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    Further practice

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    Bibliography and references