Real Life Examples of Probability and Its Applications

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Probability plays a crucial role in our daily lives, from weather forecasting to predicting election outcomes. This article explores real-life examples like weather forecasting, cricket batting average, political analysis, coin flipping, and insurance planning. Understanding probability helps in making informed decisions and assessing the likelihood of different outcomes in various situations.

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8 Real Life Examples Of Probability Probability has something to do with a chance. It is the study of things that might happen or might not. We use it most of the time, usually without thinking of it. We don t perform actual probability problems in our daily life but use subjective probability to determine the course of action or any judgment. Everything from the weather forecasting to our chance of dying in an accident is a probability.

Probability is a mathematical term for the likelihood that something will occur. It is the ability to understand and estimate the likelihood of any different combination of outcomes.

Lets discuss some real-life examples of Probability 1. Weather Forecasting Before planning for an outing or a picnic, we always check the weather forecast. Suppose it says that there is a 60% chance that rain may occur. Do you ever wonder from where this 60% come from? Meteorologists use a specific tool and technique to predict the weather forecast. They look at all the other historical database of the days, which have similar characteristics of temperature, humidity, and pressure, etc. And determine that on 60 out of 100 similar days in the past, it had rained.

2. Batting Average in Cricket 2. Batting Average in Cricket Batting average in Cricket represents how many runs a batsman would score before getting out. For example, if a batsman had scored 40 runs out of 100 from boundaries in the previous match. Then, there is a chance that he would score 40% of his runs in the next match from boundaries.

3. Politics 3. Politics Many politics analysts use the tactics of probability to predict the outcome of the election s results. For example, they may predict a certain political party to come into power; based on the results of exit polls.

4. Flipping a coin or Dice 4. Flipping a coin or Dice Flipping a coin is one of the most important events before the start of the match. There is no surety, either head will come or not. Both head and tail have 1 out of 2, i.e., 50% chances to occur. Hence, the probability of getting the desired outcome is 0.5. Similarly, while playing with dice, there are 1 out of 6 chances, that the required number will come.

5. Insurance 5. Insurance Probability helps in analyzing the best plan of insurance which suits you and your family the most. For example, you are an active smoker, and chances of getting lungs disease are higher in you. So, instead of choosing an insurance scheme for your vehicle or house, you may go for your health insurance first, because the chance of your getting sick are higher. For instance, nowadays people are getting their mobile phones insured because they know that the chances of their mobile phones getting damaged or lost are high.

6. Are we likely to die in an accident? 6. Are we likely to die in an accident? Rates of car accidents have increased rapidly in the past decades. For example, if a city has a population of one lakh, and the death rate in car accidents is 500. So, the chance of being killed in a crash is 500/1 lakh is 0.05%. Thus, a person has a 0.05% chance to die in a car accident.

7. Lottery Tickets 7. Lottery Tickets Winning or losing a lottery is one of the most interesting examples of probability. In a typical Lottery game, each player chooses six distinct numbers from a particular range. If all the six numbers on a ticket match with that of the winning lottery ticket, the ticket holder is a Jackpot winner- regardless of the order of the numbers. The probability of this happening is 1 out of 10 lakh.

8. Playing Cards 8. Playing Cards There is a probability of getting a desired card when we randomly pick one out of 52. For example, the probability of picking up an ace in a 52 deck of cards is 4/52; since there are 4 aces in the deck. The odds of picking up any other card is therefore 52/52 4/52 = 48/52.