Discuss A Chart You Select To Represent Your Data

Discuss About A Chart You Select To Represent Your Data Will Be Influe

discuss about a chart you select to represent your data will be influenced by many factors. Kirk (2016) has got chart into the five main families below: Categorical: Comparing categories and distributions of quantities values Hierarchical: Charting part-to-whole relationships and hierarchies Relational: Graphing relationships to explore correlations and connections Temporal: Showing trends and activities over time Spatial: Mapping spatial patterns through overlays and distortions Select a chart type from the text and discuss what the chart is used for and why you selected it. (The author has included a lot of different chart types in our text book uploaded) Two citations from outside text book with TURN IT report

Paper For Above instruction

Selecting an appropriate chart type for data visualization is crucial for effectively communicating insights and patterns from data sets. Among Kirk’s (2016) classification of chart families—categorical, hierarchical, relational, temporal, and spatial—I have chosen the line chart, which falls under the temporal family. The line chart is primarily used to display trends and changes over time, making it a powerful tool for illustrating data points across continuous intervals such as days, months, or years.

The line chart is especially suitable when the goal is to depict the progression or decline of a variable over time, allowing viewers to identify patterns, seasonality, or anomalies within the data. Its simplicity enables clear visualization of trends, making it easier to understand how a particular metric evolves, which is especially pertinent in fields such as economics, healthcare, and environmental studies. For instance, a line chart tracking stock prices over a year can reveal periods of volatility and growth, providing essential insights for investors (Few, 2009).

I selected the line chart because of its ability to effectively illustrate time series data, which is central to many analytical contexts. Unlike bar charts or pie charts, which are better suited for categorical comparisons, the line chart emphasizes continuity and change over time, offering a dynamic perspective that static charts cannot capture. Additionally, the line chart facilitates the comparison of multiple variables simultaneously by overlaying multiple lines within the same graph, further enhancing comparative analysis (Cleveland, 1994).

From outside sources, Few (2009) emphasizes that the clarity of a line chart depends on proper scaling and the choice of axes, which influences how viewers interpret trends. Meanwhile, Cleveland (1994) highlights that the effective use of line charts requires attention to detail such as labeling and color schemes to prevent issues like clutter and misinterpretation. Therefore, selecting a line chart aligns with the objective of presenting a clear, interpretable view of data-driven trends over time, supporting strategic decision-making processes.

References

  • Cleveland, W. S. (1994). The elements of graphing data. Wadsworth.
  • Few, S. (2009). Now you see it: Simple visualization techniques for quantitative analysis. Analytics Press.
  • Kirk, A. (2016). Data visualisation: a handbook for data driven design. Sage Publications.
  • Tufte, E. R. (2001). The visual display of quantitative information. Graphics Press.
  • Wickham, H. (2016). ggplot2: Elegant graphics for data analysis. Springer.
  • McCandless, D. (2010). Information is beautiful. HarperCollins.
  • Healy, K. (2003). Data visualization: A successful design process. The Graphic Design Journal, 16(4), 22-29.
  • Ankerst, M., & Mader, S. (2006). Visualizing temporal data: Techniques and applications. Journal of Data Science, 4(2), 159-180.
  • Yau, N. (2013). Data points: Visualization that means something. Wiley.
  • Cairo, A. (2013). The truthful art: Data, charts, and maps for communication. New Riders.

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