Computer Science Homework Help

1. Bar chart

The bar chart is also known as a column chart or histogram chart. This type of chart is the most popular and primitive chart for data visualization. The length of the chart represents the quantitative value of data(Kirk, A. (2019)). This data will give the range of quotative values of data. It is also easier to notice the outliers of data in a single glance. We can also perform a local comparison of data with the neighbor’s bar. This type of plot can be present in both vertical and horizontal formats. The trend of data can be visualized using a bar chart in series of data.

1. Bubble chart

The bubble chart is also known as a circle packing diagram. The chart displays the quantitative values of data for different categories (Kirk, A. (2019)). It uses circles, size proportion to the quantity of that they represent. Other colors are used to differentiate the data. The extensive data can be visually inferred based on the size of the data. Since data is represented as a cluster, comparing with neighbors is also very easy on such data

1. Range chart

The range chart is also known as a span chart or floating chart. The range chart displays the range of data. It includes minimum to maximum distribution of data. The length of the chart represents the limits of the data. This type of chart is helpful while finding outliers visually. Comparing the neighbor bar will give a clear idea of distinguishing between other data (Kirk, A. (2019)).

1. Kirk, A. (2019). Data Visualization: A handbook for data driven design. Los Angeles: Sage Publications.

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Answer 2

In general, storytelling in data visualization entails developing a narrative using a series of discrete sequences. Kirk (2019) has discussed several storytelling techniques in data visualization. The first example is a bullet chart, an example of a bar chart that displays quantitative values for various categories while integrating other bandings to facilitate interpretation of the bars. Bullet charts are important for visually tracking performance against target, and representing the results in a single column.

Advantages of Bullet Charts

• Can display several measures.
• It can be horizontally or vertically oriented.
• It is easy to understand displayed information.

The second storytelling technique discussed by Kirk (2019) is pictogram. A pictogram is used to illustrate quantitative values for different primary category items, and also provides the option for secondary categorical breakdown. Each point on the pictogram can be used to illustrate one or many quantitative units. Pictograms are important because they are visually engaging.

Advantages of Pictograms

1. They make data memorable and easy to comprehend.
2. They make categories legible.
3. They express large amounts of information in a simple form.

The third and final story telling technique is a word cloud. According to Kirk (2019) a word cloud illustrate the frequency of individual word items in a passage of textual data. The items are illustrated by word and then the font size of each word is scaled based on the frequency of its usage. A word cloud is important because it serves as a simple and excellent option for visually communicating the most frequent words in a document (Lohmann et al., 2015).

Advantages of Word Cloud

1. It is easy to understand the most prominent aspects in a data set.
2. It is possible to measure the audience’s understanding of the topic.

References

Kirk, A. (2019). Data visualisation : a handbook for data driven design. London Thousand Oaks, CA: SAGE Publications Ltd.

Lohmann, S., Heimerl, F., Bopp, F., Burch, M., & Ertl, T. (2015, July). Concentri cloud: Word cloud visualization for multiple text documents. In 2015 19th International Conference on Information Visualisation (pp. 114-120). IEEE.