Application of Probability Theory in Business Decision Making
Most every business decision you make relates to some aspect of probability. While your focus is on formulas and statistical calculations used to define probability, underneath these lie basic concepts that determine whether — and how much — event interactions affect probability. Together, statistical calculations and probability concepts allow you to make good business decisions, even in times of uncertainty.
About Probability, Statistics and Chance
Probability concepts are abstract ideas used to identify the degree of risk a business decision involves. In determining probability, risk is the degree to which a potential outcome differs from a benchmark expectation. You can base probability calculations on a random or full data sample. For example, consumer demand forecasts commonly use a random sampling from the target market population. However, when you’re making a purchasing decision based solely on cost, the full cost of each item determines which comes the closest to matching your cost expectation.
The concept of mutually exclusivity applies if the occurrence of one event prohibits the occurrence of another event. For example, assume you have two tasks on your to-do list. Both tasks are due today and both will take the entire day to complete. Whichever task you choose to complete means the other will remain incomplete. These two tasks can’t have the same outcome. Thus, these tasks are mutually exclusive.
A second concept refers to the impact two separate events have on each other. Dependent events are those in which the occurrence of one event affects — but doesn’t prevent — the probability of the other occurring. For example, assume a five-year goal is to purchase a new building and pay the full purchase price in cash. The expected funding source is investment returns from excess sales revenue investments. The probability of the purchase happening within the five-year period depends on whether sales revenues meet projected expectations. This makes these dependent events.
Interdependent events are those in which the occurrence of one event has no effect of the probability of another event. For example, assume consumer demand for hairbrushes is falling to an all-time low. The concept of interdependence says that declining demand for hairbrushes and the probability that demand for shampoo will also decline share no relationship. In the same way, if you intend to purchase a new building by investing personal funds instead of relying on investment returns from excess sales revenues, the purchase of a new building and sales revenues share no relationship. Thus, these are now interdependent events.