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Graphs and statistics are used to misrepresent data constantly when trying to push a product or prove a point. We see this happen primarily with truncated Y-axis’s in an attempt to visually mislead. The conventional way of creating a graph is to start your Y axis at 0 and have it go up to the highest data point in your given set. By not starting it off at 0, we create a visual illusion that makes small differences in numbers or percentages become extremely hyperbolic. This can create a prejudice or favoritism for any specific point or product. For example, with the example given below of welfare recipient, we see a visual difference between people on welfare compared to others working fulltime, illustrating a larger amount of people on welfare and further pushing the point. If the graph’s Y axis was set at 0, we would see the graph show virtually no difference in size.

Reference

The statisticians at Fox News use classic and novel graphical techniques to lead with data. (n.d.). Retrieved from https://simplystatistics.org/2012/11/26/the-statis…

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The mean is a model of your data set that reflects the value that is most common. An appropriate population to use the mean can be seen with staff salaries as long as there isn’t large differences between employee wages. It can give an accurate representation of the average salary of employees for a given company. The mean can become quickly inappropriate to use if large differences in salary are seen amongst employees. If the boss was to add his salary into the mix, a large alteration in average workers pay would be seen, displaying incorrect averages for the majority of workers. In short, the mean is unable to be accurate when extremely lows and high data points. The median is the middle score for a set of data that has been arranged in order of value, making it less affected by extreme highs and lows. When e sample size has massive numbers or outliers amongst the group, the median become a more acceptable tool but should not be used when there are very few data points available. The mode is a way of expressing, in a single number or important information about a random variable or a population. One of the problems with the mode is that it is not unique, so it leaves us with problems when we have two or more values that share the highest frequency.

Reference
Mertler, C. A., & Reinhart, R. V. (2016). Advanced and multivariate statistical methods: Practical application and interpretation. Routledge.