What is Survivorship Bias?
In daily life, you must have heard some people conclude that 'studying is useless because they have seen cases of people who didn't have a good academic experience or degree but still succeeded in their careers. But they ignore those who are silent and lost because they did not go to school properly. Those who lost their souls because they did not study well.
Many people always lament that movie production is 'not as good as it used to be' after watching old classic movies, but they ignore the old, unpopular movies that have been eliminated in time.....
This is survivorship bias.
When doing research on survivorship bias, one example that will appear frequently on the result page is the airplane of World War 2. At that time, experts were invited to study the best way to protect airplanes from being destroyed by enemies. The experts started their analysis based on airplanes returning from combat to see the parts that got shot the most. Later on, experts realized that they had fallen into survivorship bias: they ignored those that didn’t get to come back from the combat and only observed those that survived.
What Exactly is Survivorship Bias?
Survivorship bias happens when a visible successful subgroup is being thought as an entire group because of the failure subgroup being invisible. This allows viewers to falsely believe that they will succeed because of the biased fact they saw. The phenomenon usually occurs in situations such as in epidemiology and business.
Using COVID-19 as an example, people who died because of COVID while not being tested do not count towards the death count. This can form into a bias skewing the effect of the disease. Similarly, by only looking at successful start-up founders such as Steve Jobs and Bill Gates, people often assume that start-ups have a high success rate.
How Do We Avoid Survivorship Bias?
So how can we avoid survivorship bias or the impact of survivorship bias? To prevent survivorship bias, people must be very careful about which data they own. People must ensure that the data resources they choose do not create missed opportunities. In other words, we should view and treat a thing from many aspects and try to get a clear understanding of an event. In this way, survivorship bias can be avoided and the impact of survivorship bias can be avoided.
The classic example of survivorship bias occurred in World War II: specialists had to figure out how to avoid destroying aircraft. But the specialists didn't look at the crashed planes; they only looked at the ones that survived. When the successful group is presented and the failure group is hidden, the survivorship bias occurs. In order to avoid survivorship bias, we need to be cautious with the data we have and make sure it doesn't lead to missed chances.
We can also accomplish this by looking at things from several sides to obtain a clearer perspective!
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