Probability, is one of the factors that most affects our economic decision-making. We all use it sometimes without being aware were using it are we using it well.

A simple concept

Probability seems like a simple concept: the likelihood that something will happen, but how we should use probability in our decision-making seems equally simple. If an outcome has 100% chance of occurring we should treat that outcome is twice as important as one that only has a 50% chance and four times as important as one that has a 25% chance and 100 times a point important is a 1% chance.

In essence we should judge probabilities accurately and allow them to influence their decision-making in a mathematically consistent manner, but we don’t we show systematic biases and how we judge and use probabilities. But, why is it so difficult for us to judge the probability of events and why do we fail to use probability information effectively even when it is given to us.

Probability weighting

To gain answers to these questions will need to explore the phenomenon of probability weighting which describes the bias people show when working with probability. This phenomenon was along with reference dependence one of the two main advances in prospect theory and thus probability weighting is one of the foundational concepts in behavioral economics.

Biases and probability judgments arise naturally just from the statistics the world around us. In fact there is a specific probability weighting function that mathematically describes how people tend to convert objective information into a subjective sense of probability. These biases in the use of probability are endemic to every aspect of our decision-making from gambling the public policy to insurance and many many others.

Describing something’s probability

It turns out that there are worse and better ways to think about probability. The usual way is rife with bias and error, but by the end of this lecture you understand some different ways of thinking about probability. They may seem counterintuitive at first but they lead to much more accurate confident and consistent decisions.

Let’s begin by considering what we mean by probability. Probability is the likelihood that some defined event will occur. There are two common ways in which we describe something’s probability. The first is in terms of percentages, saying something like there’s an 80% chance of rain tomorrow. That’s the way this seems most natural to people and all use percentages in the bulk of this lecture.

But, there’s a second way in terms of frequency saying something like 4 out 5 dentists recommend flossing daily. Frequency might seem like just a more complex way of stating a percentage after all the two are mathematically equivalent but there are important differences between thinking in terms of percentages and thinking in terms of frequencies and those differences will be important at the end.

Probabilities are only meaningful insofar as the events they describe are well defined. If you flip a fair coin there is a 50% chance it will land heads in a 50% chance it will land tales. These two events are exclusive you can either flip heads or flip tales but you can’t do both. They are also exhaustive, the sum of their two individual probabilities sums up to exactly 100%. Many other real world events are similarly well-defined.

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