Magic number 7+-2: Definition & Examples | Cognitive Biases

What is the Magic number 7+-2 bias? There is a cognitive bias that says « We remember best the first and last items in a series, and the middle items are forgotten or remembered as average ». This website explains what it means. We also have an online test to check if you suffer from this bias.

Zero-sum bias: Definition & Examples | Cognitive Biases

What is the zero-sum bias? The zero-sum bias is a cognitive bias that describes the tendency of people to see situations as fixed quantities, so whoever ends up with the most must have taken it from someone else. This cognitive biases can affect negotiations or group dynamics where participants may feel animosity towards other parties involved.

Murphy’s Law: Definition & Examples | Cognitive Biases

What is the Murphy’s Law? This law states that if something can go wrong then it will. It works by assuming that bad things are more likely to happen at inconvenient times. This means that having something important to do will be just around other distractions and someone else will disturb you during the task.

Normalcy biasy: Definition & Examples | Cognitive Biases

What is the Normalcy bias? Normalcy bias is human inclination to ignore the possibility of risk. In other words, if something bad doesn’t happen for a long time – we believe that nothing bad will ever happen in future either. This article focuses on definition and examples of normalcy bias . How does it work?Lire la suite « Normalcy biasy: Definition & Examples | Cognitive Biases »

Appeal to probability fallacy: Definition & Examples | Cognitive Biases

What is the Appeal to probability fallacy? The ‘Appeal to probability fallacy’ is an argument that uses probability fallaciously. For example, it might be argued that something will definitely happen because there’s a high chance it will happen. This is the appeal to probability fallacy because, while something may very well happen, using its probability of happening as evidence for its occurrence is logically flawed.

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