In our everyday life, the term “probability” is commonly used. Sure, you have heard lines such as “probably, he may come today” and “probably you’re right.” From the layman’s standpoint, probability is synonymous with terms like “chance” and “possibility.” However, from a statistical point of view, probability is associated with a particular connotation.
Probability Broken Down
Probability refers to the extent to which an event is likely to take place. This likelihood is usually quantified as a percentage between 0 and 100 or any number between 0 and 1. To speak loosely, 0 and 1 denote total impossibility and total certainty respectively. If the probability of an event is high, the chances that it will occur are also high and vice versa.
If you flip or toss a coin, there are only two possibilities: the coil will either land on its tail or head, period! The coin is unbiased (fair); hence, the likelihood of either outcome is 50/50. In other words, the probability that the coin will land on its head when tossed is equal to the probability that it will land on its tail. But how can we work this out? It is simple: probability of an event occurring= the number of times the event can occur / the total number of all possible outcomes.
Why Probability Is Important
The probability theory was developed in the 17th century and has its origin from such things as flipping coins, drawing cards from packs, and throwing dices. Today, the concept of probability has a lot of significance in our daily life. First of all, it is the basis upon which the analysis of statistics is premised. Other benefits of probability include the following:
- It plays a major role in decision making
- It is important in planning and preventing the occurrence of bad events, including accidents and food shortage
- It helps in making important predictions in research