3 Common Statistical Biases Everyone Falls Prey To [Math Mondays]
These biases affect us in all kinds of way- whether you're a statistician or not
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Statistics are powerful tools for understanding the world and making informed decisions. However, statistics can also be misleading or inaccurate if they are affected by bias. Bias is anything that leads to a systematic difference between the true parameters of a population and the statistics used to estimate those parameters. In other words, bias refers to a flaw in the experiment design or data collection process, which generates results that don't accurately represent the population.
However, bias is a problem, even if you aren’t directly doing a lot of math. Our minds fall prey to such biases all the time, which are exploited by politicians, sales people, and other people trying to influence our thoughts. By becoming more aware of these issues, you can fight your biases and be harder to manipulate.
3 Biases to Look Out For
Selection Bias- Selection bias occurs when you are selecting your sample or your data wrong. Usually, this means accidentally working with a specific subset of your audience instead of the whole, rendering your sample unrepresentative of the whole population. There are many underlying reasons, but by far the most typical is collecting and working only with data that is easy to access.
This is problematic because it skews your conclusions and can lead to you making terrible investments. The Crypto Crash, which I covered here, is the perfect example of how selection bias-focusing on some people making millions- was used to hide the larger image of poverty.
Recall Bias- Recall bias occurs when people's memories are inaccurate or incomplete, which affects how they report their past experiences or behaviors. This can happen for various reasons, such as forgetting details, exaggerating events, suppressing negative emotions, or being influenced by external factors.
This is a favorite of biased news media outlets, that continuously push certain narratives in your mind to influence your opinions. If I can flood your mind with stories pushing one side, then you won’t look at the other perspectives.
Observer Bias- Observer bias occurs when the person who is collecting or analyzing the data has expectations or preferences that influence how they interpret or reports the data. This can happen consciously or unconsciously and can affect both qualitative and quantitative data.
My universities professor evaluations are a perfect example of this. We can only fill out professor evals at the end of our semesters. By this time, people who struggled with the course and/or with the professor have already dropped out. So we’re left with people who are more likely to not complain.
Combating each of these involves slowing down and evaluating any claims/studies holistically. They prey on your mind’s tendency to rush through nuances. So by slowing down, you will be able to fortify yourself. Almost an year ago, I did a post on attentional blindness. That will serve you well. This post contains a personal story of how attentional blindness led to me messing up my first-ever ‘senior’ interview. To know more, read the story below
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