Survivorship Bias — Abraham Wald and the WWII Airplanes

Survivorship bias is a tricky fal­lacy to deal with.

We’re all mes­mer­ised by suc­cess stor­ies. But study­ing those who are suc­cess­ful isn’t always the best idea.

You might suc­cumb to sur­viv­or­ship bias.
You might bet on flawed strategies.

Here goes:

Abraham Wald and the Allied Aircrafts

During World War II, the Allies stud­ied Nazi dam­age to their fight­er planes. Their study res­ul­ted in this dot­ted illustration:

The ana­lys­is of these dam­ages res­ul­ted in the idea that the Allied Forces should rein­force their fight­er planes in the areas show­ing the densest clusters of red dots. 

A stat­ist­i­cian by the name of Abraham Wald dis­agreed. Instead, he sug­ges­ted that they rein­force sur­faces with no red dots. Wald was right, of course. The red-dot­ted areas indic­ated non-fatal dam­aged regions by study­ing planes that some­how returned home. 

If it had been pos­sible to study all the planes shot down and des­troyed by the Nazis, maybe the research team would have found an inverse pattern?

“Wald’s work on air­craft vul­ner­ab­il­ity, using data from sur­viv­ors, was cru­cial in World War II, Korea, and Vietnam, and has been reis­sued by the Center for Naval Analyses.”
Source: Journal of the American Statistical Association ¹Mangel, M., & Samaniego, F. (1984). Abraham Wald’s Work on Aircraft Survivability. Journal of the American Statistical Association, 79, 259 – 267. https://​doi​.org/​1​0​.​1​0​8​0​/​0​1​6​2​1​4​5​9​.​1​9​8​4​.​1​0​4​7​8​038

World War I and the Soldiers’ Helmets

In anoth­er example, we focus on a seem­ingly coun­ter­in­tu­it­ive phe­nomen­on that emerged dur­ing World War I. 

As mil­it­ary forces began to increase the issu­ing of hel­mets to sol­diers to pro­tect them from the per­ils of the bat­tle­field, an unex­pec­ted trend was observed: the num­ber of wounded sol­diers surged dramatically. 

At first glance, it may seem that the hel­mets were para­dox­ic­ally mak­ing it easi­er for more people to get hurt. The crux of this para­dox lies in the shift­ing dynam­ics of the cas­u­alty statistics: 

As hel­mets were intro­duced and dis­trib­uted more widely, they sig­ni­fic­antly reduced the num­ber of fatal­it­ies on the bat­tle­field. Soldiers who would have pre­vi­ously suc­cumbed to their injur­ies were now sur­viv­ing. Consequently, these sol­diers were clas­si­fied as “wounded” rather than “dead.”

This shift in cat­egor­isa­tion cre­ated the illu­sion of increased injur­ies when, in real­ity, the num­ber of fatal­it­ies had decreased. 

The Fallacy of Survivorship Bias

These examples under­score the import­ance of con­sid­er­ing the lar­ger con­text and being cau­tious about con­clu­sions based solely on super­fi­cial data.

Both stor­ies are excel­lent examples of a par­tic­u­lar fal­lacy — sur­viv­or­ship bias.

“Survivorship bias, sur­viv­al bias is the logic­al error of con­cen­trat­ing on entit­ies that passed a selec­tion pro­cess while over­look­ing those that did not. This can lead to incor­rect con­clu­sions because of incom­plete data.”
Source: Wikipedia ²Survivorship bias. (2023, October 9). In Wikipedia. https://​en​.wiki​pe​dia​.org/​w​i​k​i​/​S​u​r​v​i​v​o​r​s​h​i​p​_​b​ias

We often can’t help being enticed by suc­cess stor­ies in pop­u­lar cul­ture and busi­ness. But their stor­ies can lead us to fal­la­cious conclusions. 

Few think to study those who turned out to be unsuc­cess­ful. This is too bad for data sets since the unsuc­cess­ful typ­ic­ally out­num­ber the suc­cess­ful by a vast margin.

PR Resource: Logical Fallacies and Biases

List of Logical Fallacies and Biases

As humans, we often fall for the tricks our own psy­cho­logy plays on us. These “think­ing errors” exist because they’ve often aided our sur­viv­al. However, know­ing and under­stand­ing vari­ous types of com­mon fal­la­cies and biases is help­ful in every­day life.

Here are a few examples of logic­al fal­la­cies and biases that I’ve come across while study­ing pub­lic rela­tions and linguistics:

• Fallacy of Composition
• Fallacy of Division
• The Gambler’s Fallacy
• Tu Quoque (Who Are You To Talk?)
• Strawman
• Ad Hominem
• Genetic Fallacy (Fallacy of Origin or Fallacy of Virtue)
• Fallacious Appeal to Authority
• Red Herring
• Appeal to Emotion
• Appeal to Popularity (The Bandwagon Effect)
• Appeal to Tradition
• Appeal to Nature
• Appeal to Ignorance
• Begging the Question
• Equivocation
• False Dichotomy (Black or White)
• Middle Ground Fallacy
• Decision Point Fallacy (Sorites Paradox)
• Slippery Slope Fallacy
• Hasty Generalisations (Anecdotal Evidence)
• Faulty Analogy
• Burden of Proof
• Affirming the Consequent
• Denying the Antecedent (Fallacy of the Inverse)
• Moving the Goalposts
• No True Scotsman
• Personal Incredulity
• False Causality
• Texas Sharpshooter
• Loaded Question
• Chesterton’s Fence
• Survivorship Bias
• Dunning-Kruger Effect
• Confirmation Bias
• Heuristic Anchoring
• Curse of Knowledge
• Optimism/​Pessimism Bias
• Sunk Cost Fallacy
• Negativity Bias
• Declinism
• Backfire Effect (Conversion Theory)
• Fundamental Attribution Error
• In-Group Bias
• Forer Effect (Barnum Effect)
• Cognitive Dissonance
• Hostile Media Effect
• Cherry-Picking (The Fallacy of Incomplete Evidence)
• Spiral of Silence
• Yes Ladder
• Bystander Effect
• Reciprocation Effect
• Commitment and Consistency
• Fallacy of Social Proof
• Liking and Likeness
• Appeal to Authority
• Principle of Scarcity (FOMO)
• Loss Aversion

Learn more: 58 Logical Fallacies and Biases

💡 Subscribe and get a free ebook on how to get bet­ter PR ideas.