Everybody is subject to biases and it can have a big impact on our decisions.
The only simple way to avoid them is to know them. So let’s have a look at a few of them.
The Halo effect:
The Halo effect is the tendency for positive impressions of a person, company, brand or product in one area to positively influence one’s opinion or feelings in other areas.
- USA presidents (the American presidents were on average 8 cm taller then American people, likely because people tend to see tall people as leaders)
Average of 175 cm for the American population vs 183 cm for American presidents.
- The salaries in USA are on average 300$ higher per each cm per year
- How we judge personality based physical attraction
- In justice, people were asked to judge someone based on a text describing the event and a picture joined to the text. The experiment was done with the same text but two different pictures.
Here are the results:
The Anchor effect:
By first posing a closed-ended question you can anchor someone’s answer for the next following question.
For example a group of people were asked the following question:
- Is a blue whale larger than 49 meters?
- What the average length of a blue whale?
The average answer for the second question in usually around 60 meters
We if ask only the second question people tend to say around 30 meters.
You might think that defining a value in the first question is similar to giving a hint, but scientific experiences shows it is not the case.
The experience was the following: we spin a wheel with numbers ranging from 0 to 100 in front of peoples and then use that number in the following question: “Is there more than X% of African countries in the world? ” and then “How many African countries are there?”
In order to show the anchor effect the wheel was rigged and was always choosing 10 or 65.
The average answer for people who got the number 10 from the wheel was 25% and the answer from the people who drew the number 65 from the wheel was 45%.
Sunk cost also known as the Concorde fallacy:
A sunk cost is a sum paid in the past that is no longer relevant to decisions about the future.
For example, you booked a trip in the mountains for the weekend to do skying and it cost you 1000£, unfortunately a few days prior to the trip you find out that the weather is going to be terrible but because you paid your trip 1000£ you are likely to still chose to go even though you could stay home and watch Netflix and have a better time. Since that money is gone it shouldn’t be a factor in your decision.
This bias is a very strong one and as a big impact in many fields, such as investment decision, political decisions etc…
For example, the USA government gave argument to not stop the war in Vietnam for the reason that if they did, all the life lost during that war would have been lost for nothing.
Another example from the NBA.
The first picks in the Draft are given a lot more playing time than players drafted later having equal performances.
Loss / Endowment Bias
We value things that we have more than the things that we don’t have.
For example, let’s say you buy a concert ticket for 40£ but you wouldn’t have spent more than 50£ for this ticket. Then the price increasing to 200£ as you get close to the date of the concert. Would you sell it? Maybe not.
Example: You have to register for online course.
Case 1: The price is 195£ and if you pay it before the end of the month you get a 50£ discount.
Case 2: The price is 145£ but you get a 50£ penalty if you pay after the last day of this month.
In that situation only 67% of participants register early in case 1 trial and 93% registered early in case 2.
Another example from the Olympics:
This kind of picture is quite common in the Olympics, the person who got the 2nd place is quite often less happy than the person who got third, because their point of reference are different, the 3rd person is happy to get a medal, but the 2nd is feeling like he could have gotten the gold medal and therefore is disappointed.
The Allais paradox:
Problem 1 : 3000£ with a 0.2% chance or 6000£ with a 0.1% chance
Problem 2 : 0.2% chance to go to the second step and then 3000£ all the time or 6000£ 50% of the time.
Most people misinterpret percentages:
Here is a graph representing how people tend to perceive percentages
You might have read the following sentence in the past.
“Lottery is a tax on people who don’t understand probabilities”
Knowing what type of biases exist can help you take better decisions.
Just showing predictions as percentages could be misinterpreted.
Use relative percentages instead of absolute ones.