What is Probability and Different Types of Probability

Assume you're playing darts and you're shooting at a certain angle on the dart board. A mathematician with knowledge of the game observes a few things and concludes that you have a 52 percent chance of hitting the brown space, a 20 percent chance of hitting the blue space, a 28 percent chance of hitting the green space, and a 0 percent chance of hitting the yellow space. The question now becomes, "How did he measure probability?" And how would you go about doing it? If you are having any problem in understanding probability we are here for Probability homework Help.

What is probability?

Probability is the fascinating branch of mathematics concerned with the result of a random case. The term "probability" refers to the likelihood or expectation of a particular outcome. It describes the likelihood of a specific event occurring. We often use phrases like ‘It will most likely rain today,' ‘he will most likely pass the test,' ‘there is very little chance of a storm tonight,' and ‘most likely the price of onion will rise again.' We use the word possibility instead of terms like chance, doubt, maybe, possibly, and so on in all of these sentences.

There are three major types of probabilities

1. Theoretical Probability

With access to statistical data about an event, accurate predictions about the event can be made. In statistics, probability is defined as the likelihood of a particular outcome occurring.

If you want to know the theoretical likelihood of rolling a die and having the number '5,' you can first calculate the number of potential outcomes. We know that a die has six numbers (i.e. 1,2,3,4,5,6), so the number of potential outcomes is six as well. So, the probability of rolling a six on a die is one in six, or 1:6. Similarly, we know that flipping a coin has a total of two potential outcomes so you can get either head or tail.

As a result, the theoretical chance of landing on your head while flipping a coin is 1/2 percent.

2. Experimental Probability

Unlike theoretical probability, experimental probability requires the number of trials in its description statistics. If we flip a coin 30 times and get tails 12 times out of those 30, the experimental chance of having a head is 12:30. This probability measure is based on previously completed experiments. The sum of all potential results of an occurrence divided by the total number of trials equals experimental chance. For instance, if you roll a die 50 times, you'll get the number 6 three times. As a result, the chance of having six in the experiment is 6/50.

3. Axiomatic probability

Axiomatic Probability is a theory of unifying probability in which a set of rules devised by Kolmogorov is applied. This interpretation is based on three probability axioms:

• 0 ≤ P(E) ≤ 1 for any event E.

• The probability that “some event occurs” is 1. At least one event must occur.

• The sum of the probabilities of the individual events is the probability of the union of mutually exclusive events.

Formula used in probability

When the chances of and outcome occurring in a given situation are identical, the experiment or event is said to have equally probable outcomes. Rolling a die, for example, the chances of having a number are equal, but getting a red ball from a bag of four red balls and two blue balls is not.

1. On the basis of experimental formula we can say that the probability is,

P(E)= Number of trails in which the event happened / Total number of trail

2. On the basis of Theoretical Probability we can s that the probability is,

P(E)= number of outcomes favourable to E / Number of all possible outcomes of the experiment

Uses of probability

1. Weather forecasting

Before going on a trip, we always check the weather forecast. We can tell whether the day will be cloudy, sunny, stormy, or snowy by looking at the weather forecast. We make plans for the day based on the forecast. Assume that the weather forecast predicts a 75% chance of rain.

2. Agriculture

In agriculture and farming, temperature, season, and weather all play a role. We didn't have a good understanding of weather forecasting before, but now different technologies have been built for weather forecasting, allowing farmers to do a good job based on predictions.

Conclusion

Probability assists people in determining which options are secure and which are unpredictable. Of course, having a thorough understanding of probability makes this job much simpler. We will think about the possibility of potential events and plan accordingly by learning about chance.