Misleading statistical graph in mathematics.

By | September 10, 2023


Mathematics as a discipline is one of the most important field of study that helps us to represent our data set graphically such we can make a clear and accurate interpretation of our daily life activities.

This article has looked at some misleading statistical graphs in the field of mathematics and and has explained basically what is wrong with those graphs mentioned in this article.

Without doubt, a truncated or manipulated axis statistical graph is one of the misleading statistical graphs in mathematics. This graph has values on one or both axes truncated or misrepresented causing a gravelly misrepresentation of data. Let’s look at some examples below.

Supposed we have a dataset that is obtained from a monthly sale of a goods over a given year period. The values from the sale ranges from $0 to $10,000. To create a misleading statistical graph, we truncate the y-axis by starting the axis at $9000 rather $0. The y-axis of the graph will only display a small portion which will then make the difference between the values to appear much greater than the actually are. The illustration is below.

Due to the artificially truncated axis, in this graph, the difference between the sale values seem significant. Nevertheless, if we used appropriate axis and display the same dataset the true picture will emerge.


It is now evidence that the sale fluctuation is less dramatic and relatively minor.

The issue with a truncated graph is that it distract the perception of data by enlarging or minimizing the value difference. As a result, viewers are mislead to draw wrong conclusions or exaggerate the importance of certain events or trends.

READ:  4 easy steps to buy your placement card, How to check your placement, and how to self place yourself.

In conclusion, a statistical graph that is misleading can lead to a distraction of representation of data which result into misinterpretation of data. As a result, it is a good sign to carefully examine graphs to see if the represent the accurate data to avoid manipulation or misrepresentation.

Leave a Reply

Your email address will not be published. Required fields are marked *