It is essential for any individual working with data to know how to create meaningful graphical representations of it because these visualizations can help people more easily understand trends, patterns, and outliers within the data that could otherwise be overlooked when presented in tabular form. Graphs also make it easier for individuals to comprehend large datasets at once since they are visually appealing and easy to interpret which helps draw attention from those who may not be familiar with all of the underlying statistical concepts behind them. An example of a specific report that could be misinterpreted is one I found from an international education organization called OECD titled “What 15-Year-Olds Know and What They Can Do: Results From PISA 2018”. This report contains a bar chart showing average math scores by country/region on the vertical axis (ranging from 400-700) with countries/regions listed on the horizontal axis. The issue here is that many countries with lower average math scores were omitted due their score being offscreen – this makes it appear as if there was much less variability amongst countries than actually exists due to this skewed representation resulting in potential bias errors when interpreting results based on this graph alone without taking into account other sources of data or additional context around why certain nations were omitted (OECD, 2019). References OECD (2019). What 15 Year Olds Know & What They Can Do: Results From PISA 2018. Retrieved from https://www.oecd-ilibrary.org/docserver/9789264452788-en_2b04f0d6-en(accessed May 11th 2021).