Charts are widely used in business and political circles to present data and information. They are the foundation of any statistical analysis or decision-making process. However, graphs may mislead if they do not accurately reflect the underlying data. Charts that misrepresent data can significantly impact decision-making processes, costing organizations money and innocent people their jobs (Beattie et al., 1992). A graph is a graphical representation of numerical data. It is a simple way to show the differences between large data groups. A chart usually represents a raw or unvarnished number without any transformation. It is often used in business and accounting to illustrate the trends of the company’s finances, sales, and other activities.

A chart can be either static or dynamic. A static chart is static in the sense that it does not change over time. A dynamic chart, on the other hand, changes over time. For example, the number of salespeople might change over time, as might the prices of products. When reading a graph, it is essential to understand the different types of axes. The x-axis is usually labeled with the name of the variable that the chart is representing. The y-axis is generally marked with a number, which tells you how far the data points are from the origin. The vertical axis represents height or quantity (Beattie et al., 1992)

When looking at a graph, it is also essential to understand the different types of lines. A line represents a qualitative relationship between the two variables. For example, a positive line might represent a relationship where the data points on the y-axis go up as the data points on the x-axis go up. A line might also represent a quantitative relationship, where the data points on the y-axis represent a fixed number of units (Ertug et al., 2018).

(Created by Tyler Vigen)

The graph is misleading as the y-axis does not start at zero baselines but \$15 billion and 400. This should have been rectified by starting to scale at zero to show the actual trend. Another way the graph is misleading is by using two y-axes to reveal to its intended audience that there is a correlation between USA government spending on science and suicides by hanging, strangulation, and suffocation (Sheehan et al., 2015). There is no link or logical reasoning between expenditure on science, space, and technology and suicides by hanging, strangling, or suffocation. So, while this graph indicates that the two variables are related, it is an example of a misleading correlation. Some unaccounted factors could have led to an increase in the rate of suicides among the people during the time the US government did increase its spending on science, space, and technology. Some factors such as mental illness, traumatic stress, substance use and impulsivity, loss or fear of loss, hopelessness and chronic pain can result in suicides. Some people choose suicide after carefully considering all of their options. This choice is frequently influenced by the existence of a debilitating terminal condition from which there is little to no chance of recovery. These individuals are not distressed, paranoid, sentimental, or pleading for assistance (Silverman et al., 2020). They are attempting to take charge of their fate and end their own misery, which is typically only possible through death. They frequently see their decision to die by suicide as a way to hasten a death that will inevitably occur.

The unaccounted factors should have been presented in the chart, however, presenting such misleading information was to create an image in the mind of its audience that anytime the US government spends a lot on science people should expect an increase in suicide cases.Consequently, it is important to understand the meaning of the different symbols that are used on a graph. Symbols might show the strength of the relationship between the variables, the direction of the trend, or the statistical significance of the data. When looking at graphs, it is important to understand the different types of axes, lines, and symbols. Charting can be misleading and should be taken with a grain of salt.

References

Beattie, V., & Jones, M. J. (1992). The use and abuse of graphs in annual reports: theoretical framework and empirical study. Accounting and business research, 22(88), 291-303.

Ertug, G., Gruber, M., Nyberg, A., & Steensma, H. K. (2018). From the editors—A brief primer on data visualization opportunities in management research. Academy of Management Journal, 61(5), 1613-1625.

Sheehan, C. M., Rogers, R. G., & Boardman, J. D. (2015). Postmortem presence of drugs and method of violent suicide. Journal of drug issues, 45(3), 249-262.

Silverman, M. M., Barnaby, L., Mishara, B. L., & Reidenberg, D. J. (2020). Suicide prevention in the Americas. Crisis: The Journal of Crisis Intervention and Suic