How statistics can be misleading
Each day making a life decision is based on statistics because it persuasive, helping us to choose which car to buy, which food to eat, what company we should make the investment on.
Statistics are a rudimentary part of economy and culture, and many consider them accurate. It can be inherently deceiving. As the words follow “Statistics do not create themselves people have to create them”. Because there are no ideal statistics but some are near perfect.
In the marketing field, one tragedy that is commonly utilized to manipulate is to make a fallacious correlation between unrelated data.
For instance, inquire a group of school students on filling a survey, you’ll find 100% of them prefer orange jelly beans over others, because they wanted to see the world and complain on anarchists clearly depicting the thoughts of teenagers, in the same survey you’ll find people who chose pink jelly beans had the terror of overflowing toilets despite the fact that these statistics are technically accurate because anyone will tell you consuming orange jelly beans is not the cause of becoming anarchists, and pink ones will not influence the fear of cram-full toiltes.
Sometimes same data can appear to show opposite trends depending on how its categorizedan this often occurs when aggregated data coneals conditional variable that significantly influences results.
There are many factors that must be considered if you want to deduce if it is accurate then the salient points are
- cause and effect
- presentation of statistics
- sample size
The strategy of manipulating is utilized in medicine advertisements. We should contemplate the way of data collection, and the appearance of the representatives while analyzing statistics.
One thing that affects the data is the way the survey is done. For example making people yes/no queries, when observing the statistics the whole story must always be contemplated.
Statistics are often represented as graphs, which are common they allow trends, data and statistics to be present a facile to read method, but they can be deceptive, for example take a graph of hypothetical companies with similar profits, the scale of the graph will be modified to emphasize the contrast.
Manipulation of statistics is common in both inferential and probability because most of them do not comprehend that well, but it is crucial due to their facile deceptive nature.
For the main part, it is salient for people to learn how to analyze the statistics that affect their decisions, and improving the skill of comprehending the them and examining will assist.