## What is Probability?

The term *Probability* denotes the possibility of something happening. In probability, we study the chance of a random event occurring. Probability ranges from 0 to 1. Probability is also defined as the likelihood of occurring an event. P(heads) = 50% when a fair coin is flipped.

- Probability = 0: means that the outcome will not happen.
- Probability = 1: means it will happen with certainty.
- Probabilities cannot be less than 0 or greater than 1

## Example of Probability:

If you flip a fair coin four times, you might not get two heads and two tails. If you throw the identical coin 4,000 times, the results will be nearly half heads and half tails. In each given toss, the predicted theoretical probability of heads is 12 or 0.5. Even though the results of a few repetitions are unpredictable, there is a predictable pattern of outcomes when numerous repetitions are performed. You just need to divide the number of events by the number of possible outcomes.

### Probability includes:

**Conditional Probability**– The probability that a random variable will have a specific outcome, given that some other outcome has occurred. It is written as P(A|B).

P(A|B) = P(A∩B)/P(B)

**Unconditional Probability**– An unconditional probability is the possibility that one of the numerous conceivable outcomes will occur. The phrase refers to the possibility that an event will occur regardless of whether or not any other events have occurred or other conditions exist.

## Why is probability significant in quantitative research?

In everyday life, you utilise probability to make decisions when you don’t know what will happen. You won’t be doing actual probability problems much of the time; instead, you’ll use subjective probability to make decisions and choose the best course of action. It’s employed chiefly in quantitative studies. Probability is also used in risk management models. For example, in the binomial tree model, the probability of stock prices going up and down is calculated to price the options.