This article is going to be about what are the four conditions necessary for x to have a binomial distribution. The first condition is that there must be an infinite number of possible outcomes, meaning one event such as flipping a coin or rolling dice. The second condition is that the probability of success (or failure) on each trial must be constant and not zero, which means if you flip a coin it will always land either heads or tails with the same chance. Thirdly, there should be trials in order for an experiment to happen; this could also mean flips of coins or rolls of dice happening many times over. Lastly, you need independence between these trials because they cannot affect each other- so if I start out with five heads in a row and then flip a coin, I will get the same chance as if it was flipped on its own.

In order for x to have a binomial distribution, there must be an infinite number of possible outcomes (meaning one event such as flipping a coin or rolling dice), the probability of success on each trial must be constant and not zero. There should also be trials in order for an experiment to happen- this could mean flips of coins or rolls of dice happening many times over with different numbers coming up. Lastly, you need independence between these trials because they cannot affect each other so if I start out with five heads in a row and then flip two coins at once, I will get the same chance as if it was flipped on its own.

The first condition necessary is that there are an infinite number of possible outcomes meaning one event such as flipping a coin or rolling dice. The probability of success on each trial must also be constant and not zero which means that the event is either always going to happen or never will happen like in the case of tossing coins where there are two possible outcomes depending if it lands heads side up, tails side up. There should also be trials for an experiment to happen such as flips of coins happening many times over with different numbers coming up but you need independence between these trials because they cannot affect each other so if I start out with five heads in a row and then flip two coins at once, I will get the same chance as if it was flipped on its own.

The probability for the success of an event happening must be constant which means that it is either always going to happen or will never happen like in the case of tossing coins where there are two possible outcomes depending if it lands heads side up, tails side up. There should also be trials for an experiment to happen such as flips of coins happening many times over with different numbers coming out but you need independence between these trials because they cannot affect each other so if I start out with five heads in a row and then flip two coins at once, I will have the same chance as if one was flipped on its own instead.

- And finally, the probability for an event happening must be independent of what happens in other trials.
- The four conditions necessary for x to have a binomial distribution are:
- there should be many trials for an experiment with different outcomes coming out like flipping coins which is then repeated over and over again

Each trial outcome (success or failure) has the same chance at occurring as any other trial; no one outcome can affect another so if I start out with five heads in a row and flip two coins at once, my chance will remain the same as if one coin was flipped on its own instead of both being flipped together independence between these trials means that they cannot affect each other because it’s always either going to One event meaning flipping a coin or rolling dice. The probability of success on each trial has to be constant and not likely to change, meaning in the example of coins it would be that there is a 50% chance of head and a 50% chance for tail.

The trials need to happen many times over so there are more than one flip or roll at once. There also needs to be an independence between these trials because they cannot affect each other like flipping two coins at once where the outcome can’t come into play if you just flip them individually instead.

And finally when all four conditions are met, then what happens on any given trial will have binomial distribution which means every time x flips heads with probability p=50%, chances of success is . This answer is of course dependent on what x is.