Define Probability in Decision Science

In decision science, probability is the quantitative measure of the likelihood or chance of a particular event occurring, providing a framework to analyze and make decisions under uncertainty. It serves as a tool to forecast potential outcomes by modeling randomness and interpreting available data, thus enabling informed choices in situations where outcomes are not guaranteed.

Basic Concepts of Probability

1. Experiment: Any action or process that leads to a set of results. For example, flipping a coin is an experiment.
2. Outcome: A possible result of an experiment. In the case of a coin flip, the possible outcomes are heads or tails.
3. Event: A set of outcomes to which we assign a probability. An event can be a single outcome or a group of outcomes. For instance, getting heads when flipping a coin is an event.

Types of Probability

1. Theoretical Probability

Theoretical probability is based on the reasoning behind probability. It is the ratio of the number of favorable outcomes to the number of possible outcomes.

2. Experimental Probability

Experimental probability, also known as empirical probability, is based on actual experiments and real-life data. It is the ratio of the number of times an event occurs to the total number of trials.

3. Subjective Probability

Subjective probability is based on intuition, educated guesses, and estimates. It is not derived from any mathematical computation but rather from personal judgment.