What is the Importance of Probability in Statistics?


In statistics, we learn about different types of concepts which deal with a group of data as well as analysis of future predictions based on these data. Statistics is the study of collecting data, analysing it and presenting in different ways using charts, tables and graphs. Probability describes how possible it is for an event to occur. It tells the possibility of an outcome of any event.

The term probability is derived from the word ‘chance’. For example, what are the chances of scoring 100% marks in the exam by the student? This scenario is better explained by probability. For example, when a coin is tossed the probability of getting Head is ½. The probability distribution is the likelihood that a particular event will occur and based on which we can interpret new information. Therefore, if we can predict that an event can occur based on past events or available information, then it will be easy for many industries to set up plans for their growth and development for the future.

As per the Merriam-Webster dictionary, Statistics is stated as “classified facts representing the conditions of a people in a state – especially the facts that can be stated in numbers or any other tabular or classified arrangement”. And as per one of the famous statisticians, Sir Arthur Lyon Bowley, Statistics is stated as” Numerical statements of facts in any department of inquiry placed in relation to each other”.

There is a huge scope of statistics in different sectors and fields such as business, weather forecasting, medicine, geology, sociology, etc. The type of data we have at present based on different situations helps us to represent them publicly and analyse them for further business work. Also, the collection of current and past data helps to predict the probability of any event to occur in future. In weather forecasting, the concept of probability plays an important role. The weather department analyses and informs us if it will be going to rain in the coming hours or whether it will be cold or hot.

In probability theory, the law of total probability is a basic rule, relating the marginal probability and conditional probability. As per the total probability theorem, if two different events are linked with a sample space (set of outcomes of a random experiment), then the two events are mutually disjoint to each other. For example, a person has taken a job to complete in the agricultural field, where rain may occur and may not occur. Then the probability of his job to be completed with and without rain is linked to the probability that it will rain.

In the same way, there are different types of probability distributions which define the occurrence of events in certain situations. The normal probability distribution, explains estimates of natural events such as the height of population, rolling dice, tossing a coin, etc. Whereas discrete probability distributions give the probability of occurrence of events which are distinct in nature. All these probabilities, determine the future stats of events. Therefore, statistics and probability are interlinked with each other.

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