The applications of the probability theory are not limited to mathematics and sciences as it is a valuable instrument to estimate the likelihood of positive and negative outcomes both in business and everyday life. It is commonly used to make predictions in opinion polls, weather forecasts, trade in financial markets, environmental regulation and many other spheres. Probability concepts provide particular benefits for business decision-making as they allow entrepreneurs to assess the risk of losses and failures on the market.

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The two fundamental types of probability are empirical (experimental) and theoretical (classical) probability. In empirical probability, the estimates of the likelihood of a certain event are based on its observed frequency in experiments with numerous trials. Theoretical probability is calculated by mathematical formula that determines how likely a given outcome is, considering all possible outcomes. There are many cases when mathematical probability cannot be calculated and it is needed to perform experiments or rely on historical data. Some researchers also distinguish personal or subjective probability, which is based on individual assumptions about how likely an event or an outcome is. While this type of probability is the least reliable, it is often used in the financial sphere and in everyday life.

Probability distributions are tables, graphs or equations that assign probability to the event that a random variable has a certain discrete value (countable) or falls in the range of continuous values (uncountable). The likelihood of the event depends on the mean, standard deviation and variance of the probability distribution. The data on the graph or in the table can be distributed in many different ways. The normal distribution (presented with the “Bell Curve” graph) is symmetrical about the central value, with the mean being equal to the mode and the median. Normal distribution is characteristic for random variables such as human height, weight, salary, opinions, school grades and measurement errors etc.

Understanding probability distributions is important in the business world as it allows one to estimate future profitability and the risk of losses. If a company expects to gain the monthly revenue in the range of $300, 000 to $500, 000, these amounts can be used as extreme points in the sample range and, in the typical distribution, the most likely outcome will correspond to the midpoint of the range. A company can also apply probability distribution to anticipate the change in sales after the implementation of new advertisement campaign. Moreover, probability distribution allows companies to create and analyze different scenarios (worst-case, best-case and the most likely one) to subsequently adjust their work to achieve the best results.