So consider a lottery (a game of chance) wherein several outcomes are possible with defined probabilities. Since beliefs may not always be rational, studying behavior using subjective probabilities belongs to the realm of behavioral economics rather than traditional rationality-based economics. It may also depend upon a person’s state of mind. We don’t have to conduct a random experiment to actually compute the mathematical probability, as is the case with empirical probability.įinally, as strongly suggested before, subjective probability is based on a person’s beliefs and experiences, as opposed to empirical or mathematical probability. In these cases, we can figure out the probability of getting a head on a coin toss, two aces when two cards are randomly chosen from a deck of 52 cards, and so on (see the example of the dice in Chapter 2 'Risk Measurement and Metrics'). So, if one keeps a log of the number of times a computer crashes in a day and records it for 365 days, the probability of the computer crashing on a day will be the sum of all of computer crashes on a daily basis (including zeroes for days it does not crash at all) divided by 365.įor some problems, the probability can be calculated using mathematical deduction. The empirical probability of the event then equals n/ N. To compute a probability empirically, we repeat an experiment with uncertain outcomes (called a random experiment) and count the number of times the event of interest happens, say n, in the N trials of the experiment. Figuring out the chance, in mathematical terms, is the same as calculating the probability of an event. Students often do research on the instructor and try to get a “feel” for the chance that they will make a particular grade if they register for an instructor’s course.Įven though we covered some of this discussion of probability and uncertainty in Chapter 2 'Risk Measurement and Metrics', we repeat it here for reinforcement. But between these two extremes lies the world of uncertainty. In these extreme situations, no uncertainty arises with the outcomes. On the other hand, if the student attends all classes and scores 100 percent on all tests and assignments, then too only one outcome is possible, an “A” grade. When a student registers for a class but does not attend any lectures nor does any assigned work or test, only one outcome is possible: a failing grade. Notice that the analysis of probability and statistics applies only if outcomes are uncertain. The branch of science of uncertain outcomes is probability and statistics. So when we play games of dice, we are dealing with outcomes that are inherently uncertain. In this section, since we focus only on measurable uncertainty, we will not distinguish between risk and uncertainty and use the two terms interchangeably.Īs we described in Chapter 2 'Risk Measurement and Metrics', the study of uncertainty originated in games of chance.

who distinguished between risk and uncertainty, arguing that measurable uncertainty is risk. Knight, See Jochen Runde, “Clarifying Frank Knight’s Discussion of the Meaning of Risk and Uncertainty,” Cambridge Journal of Economics 22, no. The origins of the distinction go back to the Mr. The student should pick up the tools of this section, as we will apply them later.Īs we learned in the chapters Chapter 1 'The Nature of Risk: Losses and Opportunities' and Chapter 2 'Risk Measurement and Metrics', risk and uncertainty depend upon one another.Mathematical preliminaries discussed in this section form the basis for analysis of individual decision making in uncertain situations. In this section we discuss the notion of uncertainty.

Risk probability game