# 8 Real-Life Examples Of Probability

Probability is a factor that has to do with chance. It’s the study of what could happen or not happen. We employ it all the time, but usually without even thinking about it. We do not tackle real probability-related problems in our daily lives, but we use our subjective probabilities to decide the direction of our actions or make any judgment. Everything from weather forecasts to our chances of getting injured during an accident has a chance.

## Probability

The term “probability” is used mathematically and refers to the probability that something can occur. It’s the capacity to assess and understand the probabilities of any given combination of outcomes. Use a probability calculator to check the probability of an event. And it became easy to find the probability calculator online.

Let’s look at some real-world examples of Probability.

### 1. Weather Forecasting

When planning an excursion or picnic, it is always a good idea to examine the forecast for the weather. If it states that there’s a 60 chance that rain could be expected. Are you wondering what the source of this 60% comes from?

Meteorologists employ a specific method and instrument to forecast the forecast for the weather. They examine all other databases from the past days, that share the same characteristics in terms of temperatures and humidity, pressure, and more. They discover that on 60 of 100 days similar to those over the years, it rains.

### 2. Batting Average in Cricket

The Batting average in Cricket indicates how many runs a batsman could score before being let go. For instance, suppose an individual batsman scored 40 off 100 at boundaries in the last match. There is a possibility that he’ll make 40 percent of his runs in the following match using boundaries.

### 3. Politics

Many political analysts employ the method of probabilities to forecast the outcome of elections. For instance, they might forecast a specific political party to gain power based on outcomes in exit polls.

### 4. Flipping a coin or dice

Flipping a coin can be one of the most crucial events prior to the start of the game. There is no guarantee, that either head or tail will occur, not. Both are 1 out of 2 i.e. 50% chance of happening. Therefore, the chance of obtaining the desired outcome is 0.5. In the same way, when playing dice, there are only 1 out of six possibilities that the number you want to be a reality.

### 5. Insurance

Probability is a helpful tool to determine the most effective insurance plan that is suitable for your family and you the best. If, for instance, you are smokers who are active and the odds of contracting lung disease are more likely for you.

Therefore, instead of selecting an insurance plan for your house or car then you should consider the health plan first since the likelihood of being sick is greater. Today, for instance, many people are opting to have insurance for their phones as they realize that the chance of their phones being damaged or stolen is high.

### 6. Are we at risk of dying by accident?

The number of car accidents has been increasing rapidly over the last few years. For instance, if the city has an estimated population of 1 lakh and the rate of death from crashes is 500. Therefore, the probability of dying in a car crash is 500/1 lakh, which is 0.05 percent. So, an individual is given an 0.05 percent chance of dying in a car crash.

### 7. Lottery Tickets

Losing or winning a lottery is among the most intriguing instances of chance. In the regular Lottery game, each participant picks six numbers out of an arbitrary selection. If all six numbers on the ticket match with the winning lottery ticket the person who bought the ticket is the Jackpot winner, regardless of the order in which they place the numbers. The odds for this to happen is one out of 10.

### 8. Playing Cards

There is a possibility of picking a particular card in the event that we randomly choose one from 52. For instance, the chance of getting an ace from the 52 deck is 4/52 since there are 4 ace cards on the table. The probability of getting another card is 52/52 – 4/52.

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