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    1. QUESTION

    This is discussion board question.

     

    Do an online search for an example of data visualization that you think is a poor example.  This can be a graph, pictogram, scatterplot, historgram, etc. 

    In your initial discussion post:

    •    Share the link to the example.
    •    Give a brief description of the example you found.
    •    Explain why this is a poor example of data visualization.
    •    Tell what you would do to improve it. 

 

Subject Nursing Pages 2 Style APA

Answer

Poor Data Visualization

While data visualization is indeed an effective way of explaining the dataset to any audience, it is easy to be biased with a superficially inclined way in bounding their goodness to the effects they create. With the wide array of visualization features at our disposal, it is necessary to look beyond the surface understanding and appreciate the technique – especially is this an aid to data analyst. It is true that some visualizations are dazzlingly interactive; others are funny or clever, but the judgment of a good or bad visualization goes beyond the outlook to the information being presented. The various visualization techniques are fit for specific kinds of data and goals. When data visualizations go wrong, numbers mislead and, most obviously, the intended information is not passed. In this paper, a healthcare report in which visualization was utilized is critiqued for bad data visualization (retrieved from: http://www.ijabm.com/IJABM_Vol.%201,%20No.%206,%20November%202013/EFFECTS%20OF%20STRESS.pdf)

While delving on the effects of stress on the performance of nurses, the researcher used visualization technique as the analysis technique. The first criticism of the report that influences categorization as a bad visualization is on the goal. While visualization in data analytics is used to showcase descriptive attributes of the dataset, the use for inference is farfetched. To make such important conclusions from just the bar graphs is statistically unwholesome and is vulnerable to difficult questions.

Moreover, the choice to use bar graph as the best frequency chart instead of pie chart in this case makes the visualization bad. While presenting counts by category, the pie chart would be the best chart to use in presenting an overview of the number of respondents by category in various variables.

Finally, the color choice makes the visualization bad. Having a black background in visualization makes it less attractive, this is while avoiding bright colors but rather contrasting. The black and blue colors do not best present the data to captivation of an audience.

In this case, improving the visualization would be by using pie charts on a brighter background that offers a depth of options for color choice for the portions. Nevertheless, I would restrict the use of visualization to describing the dataset rather than making inference.

 

 

References

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